Teaching Bernoulli's Principle through Demonstrations

ABSTRACT

One proven strategy to help students make sense of abstract concepts is to sequence instruction so students have exploratory opportunities to investigate science before being introduced to new science explanations (Abraham and Renner 1986 Abraham, M. R. and Renner, J. W. 1986. The sequence of learning cycle activities in high school chemistry. Journal of Research in Science Teaching, 23: 121–143. [Crossref], [Web of Science ®] , [Google Scholar]; Renner, Abraham, and Birnie 1988 Renner, J. W., Abraham, M. R. and Birnie, H. H. 1988. The necessity of each phase of the learning cycle in teaching high school physics. Journal of Research in Science Teaching, 25: 39–58. [Crossref], [Web of Science ®] , [Google Scholar]). To help physical science teachers make sense of how to effectively sequence lessons, this article summarizes our experiences using an exploration–explanation sequence of instruction to teach Bernoulli's principle to prospective middle and secondary science teachers in a science methods course. We use demonstrations during our Bernoulli unit to help students go back and forth between their observations of phenomenon and what occurs on the microscopic level with what we have termed molecular talk. Students engage in guiding questions, consider their old and new understandings of science, and use evidence to construct new ideas during all stages of the lesson.     

Dynamic microtubules produce an asymmetric E-cadherin–Bazooka complex to maintain segment boundaries

Distributing junctional components around the cell periphery is key for epithelial tissue morphogenesis and homeostasis. We discovered that positioning of dynamic microtubules controls the asymmetric accumulation of E-cadherin. Microtubules are oriented preferentially along the dorso-ventral axis in Drosophila melanogaster embryonic epidermal cells, and thus more frequently contact E-cadherin at dorso-ventral cell–cell borders. This inhibits RhoGEF2, reducing membrane recruitment of Rho-kinase, and increasing a specific E-cadherin pool that is mobile when assayed by fluorescence recovery after photobleaching. This mobile E-cadherin is complexed with Bazooka/Par-3, which in turn is required for normal levels of mobile E-cadherin. Mobile E-cadherin–Bazooka prevents formation of multicellular rosette structures and cell motility across the segment border in Drosophila embryos. Altogether, the combined action of dynamic microtubules and Rho signaling determines the level and asymmetric distribution of a mobile E-cadherin–Bazooka complex, which regulates cell behavior during the generation of a patterned epithelium.     

Carbon allocation under light and nitrogen resource gradients in two model marine phytoplankton1

Marine phytoplankton have conserved elemental stoichiometry, but there can be significant deviations from this Redfield ratio. Moreover, phytoplankton allocate reduced carbon (C) to different biochemical pools based on nutritional status and light availability, adding complexity to this relationship. This allocation influences physiology, ecology, and biogeochemistry. Here, we present results on the physiological and biochemical properties of two evolutionarily distinct model marine phytoplankton, a diatom (cf. Staurosira sp. Ehrenberg) and a chlorophyte (Chlorella sp. M. Beijerinck) grown under light and nitrogen resource gradients to characterize how carbon is allocated under different energy and substrate conditions. We found that nitrogen (N)‐replete growth rate increased monotonically with light until it reached a threshold intensity (~200 μmol photons · m^?2 · s^?1). For Chlorella sp., the nitrogen quota (pg · μm^?3) was greatest below this threshold, beyond which it was reduced by the effect of N‐stress, while for Staurosira sp. there was no trend. Both species maintained constant maximum quantum yield of photosynthesis (mol C · mol photons^?1) over the range of light and N‐gradients studied (although each species used different photophysiological strategies). In both species, C:chl a (g · g^?1) increased as a function of light and N‐stress, while C:N (mol · mol^?1) and relative neutral lipid:C (rel. lipid · g^?1) were most strongly influenced by N‐stress above the threshold light intensity. These results demonstrated that the interaction of substrate (N‐availability) and energy gradients influenced C‐allocation, and that general patterns of biochemical responses may be conserved among phytoplankton; they provided a framework for predicting phytoplankton biochemical composition in ecological, biogeochemical, or biotechnological applications.     

Regulation of Phospholipase D Activity and Phosphatidic Acid Production after Purinergic (P2Y6) Receptor Stimulation

Phosphatidic acid (PA) is a lipid second messenger located at the intersection of several lipid metabolism and cell signaling events including membrane trafficking, survival, and proliferation. Generation of signaling PA has long been primarily attributed to the activation of phospholipase D (PLD). PLD catalyzes the hydrolysis of phosphatidylcholine into PA. A variety of both receptor-tyrosine kinase and G-protein-coupled receptor stimulations have been shown to lead to PLD activation and PA generation. This study focuses on profiling the PA pool upon P2Y₆ receptor signaling manipulation to determine the major PA producing enzymes. Here we show that PLD, although highly active, is not responsible for the majority of stable PA being produced upon UDP stimulation of the P2Y₆ receptor and that PA levels are tightly regulated. By following PA flux in the cell we show that PLD is involved in an initial increase in PA upon receptor stimulation; however, when PLD is blocked, the cell compensates by increasing PA production from other sources. We further delineate the P2Y₆ signaling pathway showing that phospholipase Cβ3 (PLCβ3), PLCδ1, DGKζ and PLD are all downstream of receptor activation. We also show that DGKζ is a novel negative regulator of PLD activity in this system that occurs through an inhibitory mechanism with PKCα. These results further define the downstream events resulting in PA production in the P2Y₆ receptor signaling pathway.     

Assembly and Function of the Regulator of G protein Signaling 14 (RGS14)·H-Ras Signaling Complex in Live Cells Are Regulated by Gαi1 and Gαi-linked G Protein-coupled Receptors

Regulator of G protein signaling 14 (RGS14) is a multifunctional scaffolding protein that integrates heterotrimeric G protein and H-Ras signaling pathways. RGS14 possesses an RGS domain that binds active Gα_i/o-GTP subunits to promote GTP hydrolysis and a G protein regulatory (GPR) motif that selectively binds inactive Gα_i1/3-GDP subunits to form a stable heterodimer at cellular membranes. RGS14 also contains two tandem Ras/Rap binding domains (RBDs) that bind H-Ras. Here we show that RGS14 preferentially binds activated H-Ras-GTP in live cells to enhance H-Ras cellular actions and that this interaction is regulated by inactive Gα_i1-GDP and G protein-coupled receptors (GPCRs). Using bioluminescence resonance energy transfer (BRET) in live cells, we show that RGS14-Luciferase and active H-Ras(G/V)-Venus exhibit a robust BRET signal at the plasma membrane that is markedly enhanced in the presence of inactive Gα_i1-GDP but not active Gα_i1-GTP. Active H-Ras(G/V) interacts with a native RGS14·Gα_i1 complex in brain lysates, and co-expression of RGS14 and Gα_i1 in PC12 cells greatly enhances H-Ras(G/V) stimulatory effects on neurite outgrowth. Stimulation of the Gα_i-linked α_2A-adrenergic receptor induces a conformational change in the Gα_i1·RGS14·H-Ras(G/V) complex that may allow subsequent regulation of the complex by other binding partners. Together, these findings indicate that inactive Gα_i1-GDP enhances the affinity of RGS14 for H-Ras-GTP in live cells, resulting in a ternary signaling complex that is further regulated by GPCRs.     

Neuraminidase-Inhibiting Antibody Is a Correlate of Cross-Protection against Lethal H5N1 Influenza Virus in Ferrets Immunized with Seasonal Influenza Vaccine

In preparing for the threat of a pandemic of avian H5N1 influenza virus, we need to consider the significant delay (4 to 6 months) necessary to produce a strain-matched vaccine. As some degree of cross-reactivity between seasonal influenza vaccines and H5N1 virus has been reported, this was further explored in the ferret model to determine the targets of protective immunity. Ferrets were vaccinated with two intramuscular inoculations of trivalent inactivated split influenza vaccine or subcomponent vaccines, with and without adjuvant, and later challenged with a lethal dose of A/Vietnam/1203/2004 (H5N1) influenza virus. We confirmed that vaccination with seasonal influenza vaccine afforded partial protection against lethal H5N1 challenge and showed that use of either AlPO₄ or Iscomatrix adjuvant with the vaccine resulted in complete protection against disease and death. The protection was due exclusively to the H1N1 vaccine component, and although the hemagglutinin contributed to protection, the dominant protective response was targeted toward the neuraminidase (NA) and correlated with sialic acid cleavage-inhibiting antibody titers. Purified heterologous NA formulated with Iscomatrix adjuvant was also protective. These results suggest that adjuvanted seasonal trivalent vaccine could be used as an interim measure to decrease morbidity and mortality from H5N1 prior to the availability of a specific vaccine. The data also highlight that an inducer of cross-protective immunity is the NA, a protein whose levels are not normally monitored in vaccines and whose capacity to induce immunity in recipients is not normally assessed.     

Linking Molecular and Population Processes in Mathematical Models of Quorum Sensing

Many bacteria alter their behaviors as a function of population density, via a process known as quorum sensing (QS). QS is achieved by the synthesis and detection of diffusible signal molecules, often involving complex signal transduction pathways and regulatory networks. Mathematical models have been developed to investigate a number of aspects of QS, resulting in a wide range of model structures; many have focused on either the molecular or the population scale. In this paper, I show that many published models fail to satisfy physical constraints (such as conservation of matter) or rely on a priori assumptions that may not be valid. I present new, simple models of canonical Gram-negative and Gram-positive QS systems, in both well-mixed and biofilm populations, focusing on the interaction between molecular and population processes. I show that this interaction may be crucial for several important features of QS, including bistability and the localization of QS in space. The results highlight the need to link molecular and population processes carefully in QS models, provide a general framework for understanding the behavior of complex system-specific models, and suggest new directions for both theoretical and experimental work.