Biological Systems from an Engineer’s Point of View

Mathematical modeling of the processes that pattern embryonic development (often called biological pattern formation) has a long and rich history [1,2]. These models proposed sets of hypothetical interactions, which, upon analysis, were shown to be capable of generating patterns reminiscent of those seen in the biological world, such as stripes, spots, or graded properties. Pattern formation models typically demonstrated the sufficiency of given classes of mechanisms to create patterns that mimicked a particular biological pattern or interaction. In the best cases, the models were able to make testable predictions [3], permitting them to be experimentally challenged, to be revised, and to stimulate yet more experimental tests (see review in [4]). In many other cases, however, the impact of the modeling efforts was mitigated by limitations in computer power and biochemical data. In addition, perhaps the most limiting factor was the mindset of many modelers, using Occam’s razor arguments to make the proposed models as simple as possible, which often generated intriguing patterns, but those patterns lacked the robustness exhibited by the biological system. In hindsight, one could argue that a greater attention to engineering principles would have focused attention on these shortcomings, including potential failure modes, and would have led to more complex, but more robust, models. Thus, despite a few successful cases in which modeling and experimentation worked in concert, modeling fell out of vogue as a means to motivate decisive test experiments. The recent explosion of molecular genetic, genomic, and proteomic data—as well as of quantitative imaging studies of biological tissues—has changed matters dramatically, replacing a previous dearth of molecular details with a wealth of data that are difficult to fully comprehend. This flood of new data has been accompanied by a new influx of physical scientists into biology, including engineers, physicists, and applied mathematicians [5–7]. These individuals bring with them the mindset, methodologies, and mathematical toolboxes common to their own fields, which are proving to be appropriate for analysis of biological systems. However, due to inherent complexity, biological systems seem to be like nothing previously encountered in the physical sciences. Thus, biological systems offer cutting edge problems for most scientific and engineering-related disciplines. It is therefore no wonder that there might seem to be a “bandwagon” of new biology-related research programs in departments that have traditionally focused on nonliving systems. Modeling biological interactions as dynamical systems (i.e., systems of variables changing in time) allows investigation of systems-level topics such as the robustness of patterning mechanisms, the role of feedback, and the self-regulation of size. The use of tools from engineering and applied mathematics, such as sensitivity analysis and control theory, is becoming more commonplace in biology. In addition to giving biologists some new terminology for describing their systems, such analyses are extremely useful in pointing to missing data and in testing the validity of a proposed mechanism. A paper in this issue of PLoS Biology clearly and honestly applies analytical tools to the authors’ research and obtains insights that would have been difficult if not impossible by other means [8]

Race, Redlining, and Automobile Insurance Prices

Following Becker\u27s (1993) suggestion that tests for discrimination should attempt to infer whether profits differ for products sold to minorities and nonminorities, this article tests the hypothesis that racial discrimination affects market prices of auto insurance in Missouri. Compared with tests for discrimination in lending markets, our results are less susceptible to bias from omitted variables.Controlling for available demographic and coverage- related factors, we do not find that loss ratios at the zip-code level are negatively related to percent minority population. This finding is inconsistent with the hypothesis that racial discrimination increases premiums relative to expected claim costs for minorities

Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy

The imaging of living cells and tissues using laser-scanning microscopy is offering dramatic insights into the spatial and temporal controls of biological processes. The availability of genetically encoded labels such as green fluorescent protein (GFP) offers unique opportunities by which to trace cell movements, cell signaling or gene expression dynamically in developing embryos. Two-photon laser scanning microscopy (TPLSM) is ideally suited to imaging cells in vivo due to its deeper tissue penetration and reduced phototoxicity; however, in TPLSM the excitation and emission spectra of GFP and its color variants [e.g., CyanFP (CFP); yellowFP (YFP)] are insufficiently distinct to be uniquely imaged by conventional means. To surmount such difficulties, we have combined the technologies of TPLSM and imaging spectroscopy to unambiguously identify CFP, GFP, YFP, and redFP (RFP) as well as conventional dyes, and have tested the approach in cell lines. In our approach, a liquid crystal tunable filter was used to collect the emission spectrum of each pixel within the TPLSM image. Based on the fluorescent emission spectra, supervised classification and linear unmixing analysis algorithms were used to identify the nature and relative amounts of the fluorescent proteins expressed in the cells. In a most extreme case, we have used the approach to separate GFP and fluorescein, separated by only 7 nm, and appear somewhat indistinguishable by conventional techniques. This approach offers the needed ability to concurrently image multiple colored, spectrally overlapping marker proteins within living cells

Intraday Load Forecasts with Uncertainty

We provide a comprehensive framework for forecasting five minute load using Gaussian processes with a positive definite kernel specifically designed for load forecasts. Gaussian processes are probabilistic, enabling us to draw samples from a posterior distribution and provide rigorous uncertainty estimates to complement the point forecast, an important benefit for forecast consumers. As part of the modeling process, we discuss various methods for dimension reduction and explore their use in effectively incorporating weather data to the load forecast. We provide guidance for every step of the modeling process, from model construction through optimization and model combination. We provide results on data from the largest deregulated wholesale U.S. electricity market for various periods in 2018. The process is transparent, mathematically motivated, and reproducible. The resulting model provides a probability density of five minute forecasts for 24 h

A Business Educators Guide To Transitioning To A Digital Curriculum

The authors, representing three key digital media business disciplines, present a case for how business curriculum could be updated to include a strong digital element without recreating the entire business school enterprise or spending millions on new faculty and technology. The three key disciplines are technology, law, and marketing

A lattice grain model of hillslope evolution

Thispaperdescribesandexploresanewcontinuous-timestochasticcellularautomatonmodelofhill- slope evolution. The Grain Hill model provides a computational framework with which to study slope forms that arise from stochastic disturbance and rock weathering events. The model operates on a hexagonal lattice, with cell states representing fluid, rock, and grain aggregates that are either stationary or in a state of motion in one of the six cardinal lattice directions. Cells representing near-surface soil material undergo stochastic disturbance events, in which initially stationary material is put into motion. Net downslope transport emerges from the greater likelihood for disturbed material to move downhill than to move uphill. Cells representing rock undergo stochas- tic weathering events in which the rock is converted into regolith. The model can reproduce a range of common slope forms, from fully soil mantled to rocky or partially mantled, and from convex-upward to planar shapes. An optional additional state represents large blocks that cannot be displaced upward by disturbance events. With the addition of this state, the model captures the morphology of hogbacks, scarps, and similar features. In its simplest form, the model has only three process parameters, which represent disturbance frequency, characteris- tic disturbance depth, and base-level lowering rate, respectively. Incorporating physical weathering of rock adds one additional parameter, representing the characteristic rock weathering rate. These parameters are not arbitrary but rather have a direct link with corresponding parameters in continuum theory. Comparison between observed and modeled slope forms demonstrates that the model can reproduce both the shape and scale of real hillslope profiles. Model experiments highlight the importance of regolith cover fraction in governing both the downslope mass transport rate and the rate of physical weathering. Equilibrium rocky hillslope profiles are possible even when the rate of base-level lowering exceeds the nominal bare-rock weathering rate, because increases in both slope gradient and roughness can allow for rock weathering rates that are greater than the flat-surface maximum. Examples of transient relaxation of steep, rocky slopes predict the formation of a regolith-mantled pediment that migrates headward through time while maintaining a sharp slope break

Stabilizing the Retromer Complex in a Human Stem Cell Model of Alzheimer's Disease Reduces TAU Phosphorylation Independently of Amyloid Precursor Protein.

Developing effective therapeutics for complex diseases such as late-onset, sporadic Alzheimer's disease (SAD) is difficult due to genetic and environmental heterogeneity in the human population and the limitations of existing animal models. Here, we used hiPSC-derived neurons to test a compound that stabilizes the retromer, a highly conserved multiprotein assembly that plays a pivotal role in trafficking molecules through the endosomal network. Using this human-specific system, we have confirmed previous data generated in murine models and show that retromer stabilization has a potentially beneficial effect on amyloid beta generation from human stem cell-derived neurons. We further demonstrate that manipulation of retromer complex levels within neurons affects pathogenic TAU phosphorylation in an amyloid-independent manner. Taken together, our work demonstrates that retromer stabilization is a promising candidate for therapeutic development in AD and highlights the advantages of testing novel compounds in a human-specific, neuronal system

Mixed-method study of a conceptual model of evidence-based intervention sustainment across multiple public-sector service settings.

BackgroundThis study examines sustainment of an EBI implemented in 11 United States service systems across two states, and delivered in 87 counties. The aims are to 1) determine the impact of state and county policies and contracting on EBI provision and sustainment; 2) investigate the role of public, private, and academic relationships and collaboration in long-term EBI sustainment; 3) assess organizational and provider factors that affect EBI reach/penetration, fidelity, and organizational sustainment climate; and 4) integrate findings through a collaborative process involving the investigative team, consultants, and system and community-based organization (CBO) stakeholders in order to further develop and refine a conceptual model of sustainment to guide future research and provide a resource for service systems to prepare for sustainment as the ultimate goal of the implementation process.MethodsA mixed-method prospective and retrospective design will be used. Semi-structured individual and group interviews will be used to collect information regarding influences on EBI sustainment including policies, attitudes, and practices; organizational factors and external policies affecting model implementation; involvement of or collaboration with other stakeholders; and outer- and inner-contextual supports that facilitate ongoing EBI sustainment. Document review (e.g., legislation, executive orders, regulations, monitoring data, annual reports, agendas and meeting minutes) will be used to examine the roles of state, county, and local policies in EBI sustainment. Quantitative measures will be collected via administrative data and web surveys to assess EBI reach/penetration, staff turnover, EBI model fidelity, organizational culture and climate, work attitudes, implementation leadership, sustainment climate, attitudes toward EBIs, program sustainment, and level of institutionalization. Hierarchical linear modeling will be used for quantitative analyses. Qualitative analyses will be tailored to each of the qualitative methods (e.g., document review, interviews). Qualitative and quantitative approaches will be integrated through an inclusive process that values stakeholder perspectives.DiscussionThe study of sustainment is critical to capitalizing on and benefiting from the time and fiscal investments in EBI implementation. Sustainment is also critical to realizing broad public health impact of EBI implementation. The present study takes a comprehensive mixed-method approach to understanding sustainment and refining a conceptual model of sustainment

Facile Protocol for Water-Tolerant “Frustrated Lewis Pair”-Catalyzed Hydrogenation

Despite rapid advances in the field of metal-free, “frustrated Lewis pair” (FLP)-catalyzed hydrogenation, the need for strictly anhydrous reaction conditions has hampered wide-scale uptake of this methodology. Herein, we report that, despite the generally perceived moisture sensitivity of FLPs, 1,4-dioxane solutions of B(C6F5)3 actually show appreciable moisture tolerance and can catalyze hydrogenation of a range of weakly basic substrates without the need for rigorously inert conditions. In particular, reactions can be performed directly in commercially available nonanhydrous solvents without subsequent drying or use of internal desiccants

System and method for monitoring cellular activity

A system and method for monitoring cellular activity in a cellular specimen. According to one embodiment, a plurality of excitable markers are applied to the specimen. A multi-photon laser microscope is provided to excite a region of the specimen and cause fluorescence to be radiated from the region. The radiating fluorescence is processed by a spectral analyzer to separate the fluorescence into respective wavelength bands. The respective bands of fluorescence are then collected by an array of detectors, with each detector receiving a corresponding one of the wavelength bands