Faceted wrinkling by contracting a curved boundary

Single-mode deformations of two-dimensional materials, such as the Miura-ori fold, are important to the design of deployable structures because of their robustness, but usually require careful pre-patterning of the material. Here, we show that inward contraction of a curved boundary produces a novel single-mode deformation without any pre-patterning. Using finite-element simulations of the contraction of a thin circular annular sheet, we show that these sheets wrinkle into a structure with negligible stretching energy, in which the contracted boundary forms spontaneous facets. We construct a strictly isometric wrinkled surface formed of triangles and cones that matches geometric and energy features closely, suggesting that this class of partly-faceted wrinkled deformations is isometric. Isometry favours the restriction of such deformations to a robust low-bending energy channel that avoids stretching. This class of buckling also offers a novel way to manipulate sheet morphology via boundary forces. Finally, it serves as a minimal model for illustrating the strong constraints imposed by geometry in elastic pattern formation.Comment: V3. Double column. 6 pages, 5 figures + S

Topographic De-adhesion in the Viscoelastic Limit

The superiority of many natural surfaces at resisting soft, sticky biofoulants has inspired the integration of dynamic topography with mechanical instability to promote self-cleaning artificial surfaces. The physics behind this novel mechanism is currently limited to elastic biofoulants where surface energy, bending stiffness, and topographical wavelength are key factors. However, the viscoelastic nature of many biofoulants causes a complex interplay between these factors with time-dependent characteristics such as material softening and loading rate. Here, we enrich the current elastic theory of topographic de-adhesion using analytical and finite element models to elucidate the non-linear, time-dependent interaction of three physical, dimensionless parameters: biofoulant's stiffness reduction, product of relaxation time and loading rate, and the critical strain for short-term elastic de-adhesion. Theoretical predictions, in good agreement with numerical simulations, provide insight into tuning these control parameters to optimize surface renewal via topographic de-adhesion in the viscoelastic regime

Application of Machine Learning to Sleep Stage Classification

Sleep studies are imperative to recapitulate phenotypes associated with sleep loss and uncover mechanisms contributing to psychopathology. Most often, investigators manually classify the polysomnography into vigilance states, which is time-consuming, requires extensive training, and is prone to inter-scorer variability. While many works have successfully developed automated vigilance state classifiers based on multiple EEG channels, we aim to produce an automated and open-access classifier that can reliably predict vigilance state based on a single cortical electroencephalogram (EEG) from rodents to minimize the disadvantages that accompany tethering small animals via wires to computer programs. Approximately 427 hours of continuously monitored EEG, electromyogram (EMG), and activity were labeled by a domain expert out of 571 hours of total data. Here we evaluate the performance of various machine learning techniques on classifying 10-second epochs into one of three discrete classes: paradoxical, slow-wave, or wake. Our investigations include Decision Trees, Random Forests, Naive Bayes Classifiers, Logistic Regression Classifiers, and Artificial Neural Networks. These methodologies have achieved accuracies ranging from approximately 74% to approximately 96%. Most notably, the Random Forest and the ANN achieved remarkable accuracies of 95.78% and 93.31%, respectively. Here we have shown the potential of various machine learning classifiers to automatically, accurately, and reliably classify vigilance states based on a single EEG reading and a single EMG reading.Comment: 6 pages, IEEE Annual Conf. on Computational Science & Computational Intelligence (CSCI), December 202

Adaptive and Behavioral Changes in Kynurenine 3-Monooxygenase Knockout Mice:Relevance to Psychotic Disorders

BACKGROUND: Kynurenine 3-monooxygenase converts kynurenine to 3-hydroxykynurenine, and its inhibition shunts the kynurenine pathway-which is implicated as dysfunctional in various psychiatric disorders-toward enhanced synthesis of kynurenic acid, an antagonist of both α7 nicotinic acetylcholine and N-methyl-D-aspartate receptors. Possibly as a result of reduced kynurenine 3-monooxygenase activity, elevated central nervous system levels of kynurenic acid have been found in patients with psychotic disorders, including schizophrenia. METHODS: In the present study, we investigated adaptive-and possibly regulatory-changes in mice with a targeted deletion of Kmo (Kmo-/-) and characterized the kynurenine 3-monooxygenase-deficient mice using six behavioral assays relevant for the study of schizophrenia. RESULTS: Genome-wide differential gene expression analyses in the cerebral cortex and cerebellum of these mice identified a network of schizophrenia- and psychosis-related genes, with more pronounced alterations in cerebellar tissue. Kynurenic acid levels were also increased in these brain regions in Kmo-/- mice, with significantly higher levels in the cerebellum than in the cerebrum. Kmo-/- mice exhibited impairments in contextual memory and spent less time than did controls interacting with an unfamiliar mouse in a social interaction paradigm. The mutant animals displayed increased anxiety-like behavior in the elevated plus maze and in a light/dark box. After a D-amphetamine challenge (5 mg/kg, intraperitoneal), Kmo-/- mice showed potentiated horizontal activity in the open field paradigm. CONCLUSIONS: Taken together, these results demonstrate that the elimination of Kmo in mice is associated with multiple gene and functional alterations that appear to duplicate aspects of the psychopathology of several neuropsychiatric disorders

Law of corresponding states for osmotic swelling of vesicles

As solute molecules permeate into a vesicle due to a concentration difference across its membrane, the vesicle swells through osmosis. The swelling can be divided into two stages: (a) an "ironing" stage, where the volume-to-area ratio of the vesicle increases without a significant change in its area; (b) a stretching stage, where the vesicle grows while remaining essentially spherical, until it ruptures. We show that the crossover between these two stages can be represented as a broadened continuous phase transition. Consequently, the swelling curves for different vesicles and different permeating solutes can be rescaled into a single, theoretically predicted, universal curve. Such a data collapse is demonstrated for giant unilamellar POPC vesicles, osmotically swollen due to the permeation of urea, glycerol, or ethylene glycol. We thereby gain a sensitive measurement of the solutes' membrane permeability coefficients, finding a concentration-independent coefficient for urea, while those of glycerol and ethylene glycol are found to increase with solute concentration. In addition, we use the width of the transition, as extracted from the data collapse, to infer the number of independent bending modes that affect the thermodynamics of the vesicle in the transition region.Comment: 10 page

Grabbing Water

We introduce a novel technique for grabbing water with a flexible solid. This new passive pipetting mechanism was inspired by floating flowers and relies purely on the coupling of the elasticity of thin plates and the hydrodynamic forces at the liquid interface. Developing a theoretical model has enabled us to design petal-shaped objects with maximum grabbing capacity

Understanding dynamic changes in live cell adhesion with neutron reflectometry

Neutron reflectometry (NR) was used to examine various live cells' adhesion to quartz substrates under different environmental conditions, including flow stress. To the best of our knowledge, these measurements represent the first successful visualization and quantization of the interface between live cells and a substrate with sub-nanometer resolution. In our first experiments, we examined live mouse fibroblast cells as opposed to past experiments using supported lipids, proteins, or peptide layers with no associated cells. We continued the NR studies of cell adhesion by investigating endothelial monolayers and glioblastoma cells under dynamic flow conditions. We demonstrated that neutron reflectometry is a powerful tool to study the strength of cellular layer adhesion in living tissues, which is a key factor in understanding the physiology of cell interactions and conditions leading to abnormal or disease circumstances. Continuative measurements, such as investigating changes in tumor cell — surface contact of various glioblastomas, could impact advancements in tumor treatments. In principle, this can help us to identify changes that correlate with tumor invasiveness. Pursuit of these studies can have significant medical impact on the understanding of complex biological problems and their effective treatment, e.g. for the development of targeted anti-invasive therapies

Time of Day-Dependent Alterations in Hippocampal Kynurenic Acid, Glutamate, and GABA in Adult Rats Exposed to Elevated Kynurenic Acid During Neurodevelopment

Hypofunction of glutamatergic signaling is causally linked to neurodevelopmental disorders, including psychotic disorders like schizophrenia and bipolar disorder. Kynurenic acid (KYNA) has been found to be elevated in postmortem brain tissue and cerebrospinal fluid of patients with psychotic illnesses and may be involved in the hypoglutamatergia and cognitive dysfunction experienced by these patients. As insults during the prenatal period are hypothesized to be linked to the pathophysiology of psychotic disorders, we presently utilized the embryonic kynurenine (EKyn) paradigm to induce a prenatal hit. Pregnant Wistar dams were fed chow laced with kynurenine to stimulate fetal brain KYNA elevation from embryonic day 15 to embryonic day 22. Control dams (ECon) were fed unlaced chow. Plasma and hippocampal tissue from young adult (postnatal day 56) ECon and EKyn male and female offspring were collected at the beginning of the light (Zeitgeber time, ZT 0) and dark (ZT 12) phases to assess kynurenine pathway metabolites. Hippocampal tissue was also collected at ZT 6 and ZT 18. In separate animals, in vivo microdialysis was conducted in the dorsal hippocampus to assess extracellular KYNA, glutamate, and gamma-aminobutyric acid (GABA). Biochemical analyses revealed no changes in peripheral metabolites, yet hippocampal tissue KYNA levels were significantly impacted by EKyn treatment, and increased in male EKyn offspring at ZT 6. Interestingly, extracellular hippocampal KYNA levels were only elevated in male EKyn offspring during the light phase. Decreases in extracellular glutamate levels were found in the dorsal hippocampus of EKyn male and female offspring, while decreased GABA levels were present only in males during the dark phase. The current findings suggest that the EKyn paradigm may be a useful tool for investigation of sex- and time-dependent changes in hippocampal neuromodulation elicited by prenatal KYNA elevation, which may influence behavioral phenotypes and have translational relevance to psychotic disorders

Analysis of biosurfaces by neutron reflectometry: From simple to complex interfaces

Because of its high sensitivity for light elements and the scattering contrast manipulation via isotopic substitutions, neutron reflectometry (NR) is an excellent tool for studying the structure of soft-condensed material. These materials include model biophysical systems as well as in situ living tissue at the solid–liquid interface. The penetrability of neutrons makes NR suitable for probing thin films with thicknesses of 5–5000 Å at various buried, for example, solid–liquid, interfaces [J. Daillant and A. Gibaud, Lect. Notes Phys. 770, 133 (2009); G. Fragneto-Cusani, J. Phys.: Condens. Matter 13, 4973 (2001); J. Penfold, Curr. Opin. Colloid Interface Sci. 7, 139 (2002)]. Over the past two decades, NR has evolved to become a key tool in the characterization of biological and biomimetic thin films. In the current report, the authors would like to highlight some of our recent accomplishments in utilizing NR to study highly complex systems, including in-situ experiments. Such studies will result in a much better understanding of complex biological problems, have significant medical impact by suggesting innovative treatment, and advance the development of highly functionalized biomimetic materials