Bitter taste stimuli induce differential neural codes in mouse brain.

A growing literature suggests taste stimuli commonly classified as "bitter" induce heterogeneous neural and perceptual responses. Here, the central processing of bitter stimuli was studied in mice with genetically controlled bitter taste profiles. Using these mice removed genetic heterogeneity as a factor influencing gustatory neural codes for bitter stimuli. Electrophysiological activity (spikes) was recorded from single neurons in the nucleus tractus solitarius during oral delivery of taste solutions (26 total), including concentration series of the bitter tastants quinine, denatonium benzoate, cycloheximide, and sucrose octaacetate (SOA), presented to the whole mouth for 5 s. Seventy-nine neurons were sampled; in many cases multiple cells (2 to 5) were recorded from a mouse. Results showed bitter stimuli induced variable gustatory activity. For example, although some neurons responded robustly to quinine and cycloheximide, others displayed concentration-dependent activity (p<0.05) to quinine but not cycloheximide. Differential activity to bitter stimuli was observed across multiple neurons recorded from one animal in several mice. Across all cells, quinine and denatonium induced correlated spatial responses that differed (p<0.05) from those to cycloheximide and SOA. Modeling spatiotemporal neural ensemble activity revealed responses to quinine/denatonium and cycloheximide/SOA diverged during only an early, at least 1 s wide period of the taste response. Our findings highlight how temporal features of sensory processing contribute differences among bitter taste codes and build on data suggesting heterogeneity among "bitter" stimuli, data that challenge a strict monoguesia model for the bitter quality

On the Use of Formative Measurement Specifications in Structural Equation Modeling: A Monte Carlo Simulation Study to Compare Covariance-Based and Partial Least Squares Model Estimation Methodologies

The broader goal of this paper is to provide social researchers with some analytical guidelines when investigating structural equation models (SEM) with predominantly a formative specification. This research is the first to investigate the robustness and precision of parameter estimates of a formative SEM specification. Two distinctive scenarios (normal and non-normal data scenarios) are compared with the aid of a Monte Carlo simulation study for various covariance-based structural equation modeling (CBSEM) estimators and various partial least squares path modeling (PLS-PM) weighting schemes. Thus, this research is also one of the first to compare CBSEM and PLS-PM within the same simulation study. We establish that the maximum likelihood (ML) covariance-based discrepancy function provides accurate and robust parameter estimates for the formative SEM model under investigation when the methodological assumptions are met (e.g., adequate sample size, distributional assumptions, etc.). Under these conditions, ML-CBSEM outperforms PLS-PM. We also demonstrate that the accuracy and robustness of CBSEM decreases considerably when methodological requirements are violated, whereas PLS-PM results remain comparatively robust, e.g. irrespective of the data distribution. These findings are important for researchers and practitioners when having to choose between CBSEM and PLS-PM methodologies to estimate formative SEM in their particular research situation.PLS, path modeling, covariance structure analysis, structural equation modeling, formative measurement, simulation study

On the Use of Formative Measurement Specifications in Structural Equation Modeling: A Monte Carlo Simulation Study to Compare Covariance-Based and Partial Least Squares Model Estimation Methodologies

The broader goal of this paper is to provide social researchers with some analytical guidelines when investigating structural equation models (SEM) with predominantly a formative specification. This research is the first to investigate the robustness and precision of parameter estimates of a formative SEM specification. Two distinctive scenarios (normal and non-normal data scenarios) are compared with the aid of a Monte Carlo simulation study for various covariance-based structural equation modeling (CBSEM) estimators and various partial least squares path modeling (PLS-PM) weighting schemes. Thus, this research is also one of the first to compare CBSEM and PLS-PM within the same simulation study. We establish that the maximum likelihood (ML) covariance-based discrepancy function provides accurate and robust parameter estimates for the formative SEM model under investigation when the methodological assumptions are met (e.g., adequate sample size, distributional assumptions, etc.). Under these conditions, ML-CBSEM outperforms PLS-PM. We also demonstrate that the accuracy and robustness of CBSEM decreases considerably when methodological requirements are violated, whereas PLS-PM results remain comparatively robust, e.g. irrespective of the data distribution. These findings are important for researchers and practitioners when having to choose between CBSEM and PLS-PM methodologies to estimate formative SEM in their particular research situation.marketing ;

Spatially selecting single cell for lysis using light induced electric fields

An optoelectronic tweezing (OET) device, within an integrated microfluidic channel, is used to precisely select single cells for lysis among dense populations. Cells to be lysed are exposed to higher electrical fields than their neighbours by illuminating a photoconductive film underneath them. Using beam spot sizes as low as 2.5 μm, 100% lysis efficiency is reached in <1 min allowing the targeted lysis of cells

An Analysis Of The Relationship Between Recent Electronic Data Breaches And Enacted Data Security And Privacy Legislation In The United States

The widescale adoption of electronic records in businesses and organizations has been a boon to entities throughout the world by simplifying the process of collecting, retrieving, and analyzing data. As some of the most prevalent industries in the United States, the industries of healthcare, finance, government, and education in particular make frequent use of electronic data system to increase operational efficiency. The impacts of this digitalization of organizations are not all beneficial, however, as data breaches represent a major threat to information security. Incidents of cyberattacks targeting healthcare, financial, governmental, and educational data are well- documented, and it is clear that the danger remains. Indeed, state and federal agencies regularly enact laws and legislation seeking to combat the rise of data breaches. Research was conducted in order to compare the occurrences of data breaches with the enactment of state data security and privacy legislation. The methodology used to perform the research largely consisted of collecting press releases and news reports ranging from 2010 to 2019 that announced a data breach incident. All relevant records were then categorized by industry. Likewise, state bills from the same time period were consulted to analyze enacted legislation that pertain to electronic data privacy and security. The findings of this study indicate that the healthcare industry has been the largest target of data breaches of the past decade, followed by the financial, governmental, and educational industries, respectively. Interestingly, the number of cyberattack trends impacting healthcare and government is shown to have decreased over time while those affecting finance and education has no clear pattern. A comprehensive view of data breaches across the four industries, however, suggest an inverse relationship with the enactment of relevant legislation. Indeed, with some variation, as the number of passed legislation increased over the decade, the number of breaches decreased

Thermal intermodulation backaction in a high-cooperativity optomechanical system

The pursuit of room temperature quantum optomechanics with tethered nanomechanical resonators faces stringent challenges owing to extraneous mechanical degrees of freedom. An important example is thermal intermodulation noise (TIN), a form of excess optical noise produced by mixing of thermal noise peaks. While TIN can be decoupled from the phase of the optical field, it remains indirectly coupled via radiation pressure, implying a hidden source of backaction that might overwhelm shot noise. Here we report observation of TIN backaction in a high-cooperativity, room temperature cavity optomechanical system consisting of an acoustic-frequency Si$_3$N$_4$ trampoline coupled to a Fabry-P\'{e}rot cavity. The backaction we observe exceeds thermal noise by 20 dB and radiation pressure shot noise by 40 dB, despite the thermal motion being 10 times smaller than the cavity linewidth. Our results suggest that mitigating TIN may be critical to reaching the quantum regime from room temperature in a variety of contemporary optomechanical systems.Comment: 8 pages, 5 figure

Towards cavity-free ground state cooling of an acoustic-frequency silicon nitride membrane

We demonstrate feedback cooling of a millimeter-scale, 40 kHz SiN membrane from room temperature to 5 mK (3000 phonons) using a Michelson interferometer, and discuss the challenges to ground state cooling without an optical cavity. This advance appears within reach of current membrane technology, positioning it as a compelling alternative to levitated systems for quantum sensing and fundamental weak force measurements.Comment: To be published in the Applied Optics special issue: James C. Wyant College of Optical Science

Divergent evolution of protein conformational dynamics in dihydrofolate reductase.

Molecular evolution is driven by mutations, which may affect the fitness of an organism and are then subject to natural selection or genetic drift. Analysis of primary protein sequences and tertiary structures has yielded valuable insights into the evolution of protein function, but little is known about the evolution of functional mechanisms, protein dynamics and conformational plasticity essential for activity. We characterized the atomic-level motions across divergent members of the dihydrofolate reductase (DHFR) family. Despite structural similarity, Escherichia coli and human DHFRs use different dynamic mechanisms to perform the same function, and human DHFR cannot complement DHFR-deficient E. coli cells. Identification of the primary-sequence determinants of flexibility in DHFRs from several species allowed us to propose a likely scenario for the evolution of functionally important DHFR dynamics following a pattern of divergent evolution that is tuned by cellular environment

A New Shear Estimator for Weak Lensing Observations

We present a new shear estimator for weak lensing observations which properly accounts for the effects of a realistic point spread function (PSF). Images of faint galaxies are subject to gravitational shearing followed by smearing with the instrumental and/or atmospheric PSF. We construct a `finite resolution shear operator' which when applied to an observed image has the same effect as a gravitational shear applied prior to smearing. This operator allows one to calibrate essentially any shear estimator. We then specialize to the case of weighted second moment shear estimators. We compute the shear polarizability which gives the response of an individual galaxy's polarization to a gravitational shear. We then compute the response of the population of galaxies, and thereby construct an optimal weighting scheme for combining shear estimates from galaxies of various shapes, luminosities and sizes. We define a figure of merit --- an inverse shear variance per unit solid angle --- which characterizes the quality of image data for shear measurement. The new method is tested with simulated image data. We discuss the correction for anisotropy of the PSF and propose a new technique involving measuring shapes from images which have been convolved with a re-circularizing PSF. We draw attention to a hitherto ignored noise related bias and show how this can be analyzed and corrected for. The analysis here draws heavily on the properties of real PSF's and we include as an appendix a brief review, highlighting those aspects which are relevant for weak lensing.Comment: 39 pages, 9 figure

Cluster-induced crater formation

Using molecular-dynamics simulation, we study the crater volumes induced by energetic impacts ($v= 1- 250$ km/s) of projectiles containing up to N=1000 atoms. We find that for Lennard-Jones bonded material the crater volume depends solely on the total impact energy $E$. Above a threshold \Eth, the volume rises linearly with $E$. Similar results are obtained for metallic materials. By scaling the impact energy $E$ to the target cohesive energy $U$, the crater volumes become independent of the target material. To a first approximation, the crater volume increases in proportion with the available scaled energy, $V=aE/U$. The proportionality factor $a$ is termed the cratering efficiency and assumes values of around 0.5.Comment: 9 page