Daily automated prediction of delirium risk in hospitalized patients: Model development and validation.

Background: Delirium is common in hospitalized patients and correlated with increased morbidity and mortality. Despite this, delirium is underdiagnosed, and many institutions do not have sufficient resources to consistently apply effective screening and prevention.

Objective: To develop a machine learning algorithm to identify patients at highest risk of delirium in the hospital each day in an automated fashion based on data available in the electronic medical record, reducing the barrier to large-scale delirium screening.

Development of the ADFICE_IT clinical decision support system to assist deprescribing of fall-risk increasing drugs: A user-centered design approach.

Introduction: Deprescribing fall-risk increasing drugs (FRIDs) is promising for reducing the risk of falling in older adults. Applying appropriate deprescribing in practice can be difficult due to the outcome uncertainties associated with stopping FRIDs. The ADFICE_IT intervention addresses this complexity with a clinical decision support system (CDSS) that facilitates optimum deprescribing of FRIDs by using a fall-risk prediction model, aggregation of deprescribing guidelines, and joint medication management.

Selective inhibition of small-diameter axons using infrared light.

Novel clinical treatments to target peripheral nerves are being developed which primarily use electrical current. Recently, infrared (IR) light was shown to inhibit peripheral nerves with high spatial and temporal specificity. Here, for the first time, we demonstrate that IR can selectively and reversibly inhibit small-diameter axons at lower radiant exposures than large-diameter axons.

Robustness, flexibility, and sensitivity in a multifunctional motor control model.

Motor systems must adapt to perturbations and changing conditions both within and outside the body. We refer to the ability of a system to maintain performance despite perturbations as "robustness," and the ability of a system to deploy alternative strategies that improve fitness as "flexibility." Different classes of pattern-generating circuits yield dynamics with differential sensitivities to perturbations and parameter variation.

Sensory Feedback Reduces Individuality by Increasing Variability within Subjects.

Behavioral variability is ubiquitous [1-6], yet variability is more than just noise. Indeed, humans exploit their individual motor variability to improve tracing and reaching tasks [7]. What controls motor variability? Increasing the variability of sensory input, or applying force perturbations during a task, increases task variability [8, 9].

Motor neuronal activity varies least among individuals when it matters most for behavior.

How does motor neuronal variability affect behavior? To explore this question, we quantified activity of multiple individual identified motor neurons mediating biting and swallowing in intact, behaving Aplysia californica by recording from the protractor muscle and the three nerves containing the majority of motor neurons controlling the feeding musculature. We measured multiple motor components: duration of the activity of identified motor neurons as well as their relative timing. At the same time, we measured behavioral efficacy: amplitude of grasping movement during biting and amplitude of net inward food movement during swallowing.

The significance of dynamical architecture for adaptive responses to mechanical loads during rhythmic behavior.

Many behaviors require reliably generating sequences of motor activity while adapting the activity to incoming sensory information. This process has often been conceptually explained as either fully dependent on sensory input (a chain reflex) or fully independent of sensory input (an idealized central pattern generator, or CPG), although the consensus of the field is that most neural pattern generators lie somewhere between these two extremes. Many mathematical models of neural pattern generators use limit cycles to generate the sequence of behaviors, but other models, such as a heteroclinic channel (an attracting chain of saddle points), have been suggested.

Double Potential Pulse Chronocoulometry for Detection of Plasma Membrane Cholesterol Efflux at Disk Platinum Microelectrodes.

A double potential pulse scheme is reported for observation of cholesterol efflux from the plasma membrane of a single neuron cell. Capillary Pt disk microelectrodes having a thin glass insulator allow the 10 μm diameter electrode and cell to be viewed under optical magnification. The electrode, covalently functionalized with cholesterol oxidase, is positioned in contact with the cell surface resulting in enzyme catalyzed cholesterol oxidation and efflux of cholesterol from the plasma membrane at the electrode contact site.

Efficient worm-like locomotion: slip and control of soft-bodied peristaltic robots.

In this work, we present a dynamic simulation of an earthworm-like robot moving in a pipe with radially symmetric Coulomb friction contact. Under these conditions, peristaltic locomotion is efficient if slip is minimized. We characterize ways to reduce slip-related losses in a constant-radius pipe.

From biology to mathematical models and back: teaching modeling to biology students, and biology to math and engineering students.

We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model.

Selective extracellular stimulation of individual neurons in ganglia.

Selective control of individual neurons could clarify neural functions and aid disease treatments. To target specific neurons, it may be useful to focus on ganglionic neuron clusters, which are found in the peripheral nervous system in vertebrates. Because neuron cell bodies are found primarily near the surface of invertebrate ganglia, and often found near the surface of vertebrate ganglia, we developed a technique for controlling individual neurons extracellularly using the buccal ganglia of the marine mollusc Aplysia californica as a model system.