A dynamic compartment model for xylem loading and long-distance transport of iron explains the effect of kanamycin on metal uptake in .

plants exposed to the antibiotic kanamycin (Kan) display altered metal homeostasis. Further, mutation of the WBC19 gene leads to increased sensitivity to kanamycin and changes in iron (Fe) and zinc (Zn) uptake. Here we propose a model that explain this surprising relationship between metal uptake and exposure to Kan.

Integration of biology, mathematics and computing in the classroom through the creation and repeated use of transdisciplinary modules.

The integration of biology with mathematics and computer science mandates the training of students capable of comfortably navigating among these fields. We address this formidable pedagogical challenge with the creation of transdisciplinary modules that guide students toward solving realistic problems with methods from different disciplines. Knowledge is gradually integrated as the same topic is revisited in biology, mathematics, and computer science courses.

Inference of cancer mechanisms through computational systems analysis.

Large amounts of metabolomics data have been accumulated to study metabolic alterations in cancer that allow cancer cells to synthesize molecular materials necessary for cell growth and proliferation. Although metabolic reprogramming in cancer was discovered almost a century ago, the underlying biochemical mechanisms are still unclear. We show that metabolomics data can be used to infer likely biochemical mechanisms associated with cancer.

Identification of cancer mechanisms through computational systems modeling.

Background: Colorectal cancer is one of the most prevalent causes of cancer death. It has been studied extensively for a long time, and numerous genetic and epigenetic events have been associated with the disease. However, its molecular mechanisms are still unclear.

A heuristic model of alcohol dependence.

Background: Substance dependence poses a critical health problem. Sadly, its neurobiological mechanisms are still unclear, and this lack of real understanding is reflected in insufficient treatment options. It has been hypothesized that alcohol effects are due to an imbalance between neuroexcitatory and neuroinhibitory amino acids.

Silica-coated dimers of silver nanospheres as surface-enhanced Raman scattering tags for imaging cancer cells.

Surface-enhanced Raman scattering (SERS) tags have been actively explored as a multiplexing platform for sensitive detection of biomolecules. Here, we report a new type of SERS tags that was fabricated by sequentially functionalizing dimers made of 50 nm Ag nanospheres with 4-mercaptobenzoic acid as the Raman reporter molecule, silica coating as a protective shell and antibody as a targeting ligand. These dimer-based tags give highly enhanced and reproducible Raman signals owing to the presence of a well-defined SERS hot spot at the junction between two Ag nanospheres in the dimer.

Using well-defined Ag nanocubes as substrates to quantify the spatial resolution and penetration depth of surface-enhanced Raman scattering imaging.

The multiplexing capability and high sensitivity of surface-enhanced Raman scattering (SERS) make this new imaging modality particularly attractive for rapid diagnosis. With 100 nm Ag nanocubes serving as the substrate, this work quantitatively evaluated, for the first time, some of the fundamental parameters of SERS imaging such as blur, spatial resolution and penetration depth. Our results imply that SERS is a high-resolution imaging technique with a blur value of 0.

Rotenone and paraquat perturb dopamine metabolism: A computational analysis of pesticide toxicity.

Pesticides, such as rotenone and paraquat, are suspected in the pathogenesis of Parkinson's disease (PD), whose hallmark is the progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Thus, compounds expected to play a role in the pathogenesis of PD will likely impact the function of dopaminergic neurons. To explore the relationship between pesticide exposure and dopaminergic toxicity, we developed a custom-tailored mathematical model of dopamine metabolism and utilized it to infer potential mechanisms underlying the toxicity of rotenone and paraquat, asking how these pesticides perturb specific processes.

The neurochemical mobile with non-linear interaction matrix: an exploratory computational model.

Several years ago, the "neurochemical mobile" was introduced as a visual tool for explaining the different balances between neurotransmitters in the brain and their role in mental disorders. Here we complement this concept with a non-linear computational systems model representing the direct and indirect interactions between neurotransmitters, as they have been described in the "neurochemical interaction matrix." The model is constructed within the framework of biochemical systems theory, which facilitates the mapping of numerically ill-characterized systems into a mathematical and computational construct that permits a variety of analyses.

Improving correlated SERS measurements with scanning electron microscopy: an assessment of the problem arising from the deposition of amorphous carbon.

For surface-enhanced Raman scattering (SERS) substrates with nonspherical symmetry, it is critical to correlate spectroscopy measurements with imaging by scanning electron microscopy (SEM). However, the deposition of carbon resulting from e-beam exposure during SEM imaging contaminates the surface of nanoparticles, potentially preventing their further functionalization with Raman probe molecules. In addition, the deposited carbon leads to unwanted background SERS signals.

Mesoscopic models of neurotransmission as intermediates between disease simulators and tools for discovering design principles.

Two grand challenges have been declared as premier goals of computational systems biology. The first is the discovery of network motifs and design principles that help us understand and rationalize why biological systems are organized in the manner we encounter them rather than in a different fashion. The second goal is the development of computational models supporting the investigation of complex systems, in particular, as simulation platforms in personalized medicine and predictive health.

Effects of dopamine and glutamate on synaptic plasticity: a computational modeling approach for drug abuse as comorbidity in mood disorders.

Major depressive disorder (MDD) affects about 16% of the general population and is a leading cause of death in the United States and around the world. Aggravating the situation is the fact that "drug use disorders" are highly comorbid in MDD patients, and VICE VERSA. Drug use and MDD share a common component, the dopamine system, which is critical in many motivation and reward processes, as well as in the regulation of stress responses in MDD.

Computational modeling of synaptic neurotransmission as a tool for assessing dopamine hypotheses of schizophrenia.

Schizophrenia is a severe and complex mental disorder that causes an enormous societal and financial burden. Following the identification of dopamine as a neurotransmitter and the invention of antipsychotic drugs, the dopamine hypothesis was formulated to suggest hyperdopaminergia as the cause of schizophrenia. Over time there have been modifications and improvements to the dopamine-based model of schizophrenia, as well as models that do not implicate dopamine dysregulation as a primary cause of the disease.

The internal state of medium spiny neurons varies in response to different input signals.

Background: Parkinson's disease, schizophrenia, Huntington's chorea and drug addiction are manifestations of malfunctioning neurons within the striatum region at the base of the human forebrain. A key component of these neurons is the protein DARPP-32, which receives and processes various types of dopamine and glutamate inputs and translates them into specific biochemical, cellular, physiological, and behavioral responses. DARPP-32's unique capacity of faithfully converting distinct neurotransmitter signals into appropriate responses is achieved through a complex phosphorylation-dephosphorylation system that evades intuition and predictability.

Computational systems analysis of dopamine metabolism.

A prominent feature of Parkinson's disease (PD) is the loss of dopamine in the striatum, and many therapeutic interventions for the disease are aimed at restoring dopamine signaling. Dopamine signaling includes the synthesis, storage, release, and recycling of dopamine in the presynaptic terminal and activation of pre- and post-synaptic receptors and various downstream signaling cascades. As an aid that might facilitate our understanding of dopamine dynamics in the pathogenesis and treatment in PD, we have begun to merge currently available information and expert knowledge regarding presynaptic dopamine homeostasis into a computational model, following the guidelines of biochemical systems theory.