Erythroid anion transporter assembly is mediated by a developmentally regulated recruitment onto a preassembled membrane cytoskeleton

Analysis of the expression and assembly of the anion transporter by metabolic pulse-chase and steady-state protein and RNA measurements reveals that the extent of association of band 3 with the membrane cytoskeleton varies during chicken embryonic development. Pulse-chase studies have indicated that band 3 polypeptides do not associate with the membrane cytoskeleton until they have been transported to the plasma membrane. At this time, band 3 polypeptides are slowly recruited, over a period of hours, onto a preassembled membrane cytoskeletal network and the extent of this cytoskeletal assembly is developmentally regulated. Only 3% of the band 3 polypeptides are cytoskeletal-associated in 4-d erythroid cells vs. 93% in 10-d erythroid cells and 36% in 15-d erythroid cells. This observed variation appears to be regulated primarily at the level of recruitment onto the membrane cytoskeleton rather than by different transport kinetics to the membrane or differential turnover of the soluble and insoluble polypeptides and is not dependent upon the lineage or stage of differentiation of the erythroid cells. Steady-state protein and RNA analyses indicate that the low levels of cytoskeletal band 3 very early in development most likely result from limiting amounts of ankyrin and protein 4.1, the membrane cytoskeletal binding sites for band 3. As embryonic development proceeds, ankyrin and protein 4.1 levels increase with a concurrent rise in the level of cytoskeletal band 3 until, on day 10 of development, virtually all of the band 3 polypeptides are cytoskeletal bound. After day 10, the levels of total and cytoskeletal band 3 decline, whereas ankyrin and protein 4.1 continue to accumulate until day 18, indicating that the cytoskeletal association of band 3 is not regulated solely by the availability of membrane cytoskeletal binding sites at later stages of development. Thus, multiple mechanisms appear to regulate the recruitment of band 3 onto the erythroid membrane cytoskeleton during chicken embryonic development

Cutoff for the noisy voter model

Given a continuous time Markov Chain $\{q(x,y)\}$ on a finite set $S$, the associated noisy voter model is the continuous time Markov chain on $\{0,1\}^S$, which evolves in the following way: (1) for each two sites $x$ and $y$ in $S$, the state at site $x$ changes to the value of the state at site $y$ at rate $q(x,y)$; (2) each site rerandomizes its state at rate 1. We show that if there is a uniform bound on the rates $\{q(x,y)\}$ and the corresponding stationary distributions are almost uniform, then the mixing time has a sharp cutoff at time $\log|S|/2$ with a window of order 1. Lubetzky and Sly proved cutoff with a window of order 1 for the stochastic Ising model on toroids; we obtain the special case of their result for the cycle as a consequence of our result. Finally, we consider the model on a star and demonstrate the surprising phenomenon that the time it takes for the chain started at all ones to become close in total variation to the chain started at all zeros is of smaller order than the mixing time.Comment: Published at http://dx.doi.org/10.1214/15-AAP1108 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Call to Lead: Educating Ethical, Moral Legal Professionals

25th anniversary reflectio

Defining a New Medium of Communication under the First Amendment: The Supreme Court Tackles Speech on the Internet in Reno v. American Civil Liberties Union

The Internet\u27 has revolutionized the exchange of information by providing our society with a new marketplace of ideas. 2 As history has revealed, new methods of communication lead to differences in opinion

To Err is Human? How Typographical and Orthographical Errors Affect Perceptions of Online Reviewers

Consumers increasingly rely on online product reviews when making purchase decisions. However, assessing the credibility of online reviewers presents consumers with unique challenges. This paper examines how consumer perceptions of reviewer credibility are influenced by the presence and type of textual errors in the review itself. The results of an online experiment indicate that consumers’ reactions to textual errors are moderated by their general trust in others. Low-trust consumers are relatively insensitive to textual errors in judging reviewer credibility. However, high-trust consumers are less forgiving of typographical errors (which may signal carelessness) than orthographical errors (which may indicate cognitive challenges). Implications for future research are discussed

COMMUNITY PREFERENCES FOR TYPES OF BUSINESSES: A CASE STUDY OF THREE COUNTIES

Community/Rural/Urban Development,

Evaluation and Comparison of Wearable Technology Device Data Between Devices During Trail Running

An estimated 20 million people participate in trail running with this number expected grow at a rate of 15% annually. Wearable technology devices have become more relied upon to track running data such as distance, cadence, elevation gain, etc. The consistency between these devices is not well-established. PURPOSE: To determine the consistency of data across wearable technology devices. METHODS: Seventeen participants (F = 7) ran on the Thunderbird Gardens Lighting Switch trail in Cedar City, UT. The participants were each fitted with two Garmin Instincts, two Polar Vantage M2s, and two Stryd sensors. One device from each manufacturer was placed on the left side (wrist for watches and foot for Stryd), and the other devices were placed on the right. Each pair of devices was started simultaneously, and the participant then completed a self-paced out-and-back trail run of approximately 20 minutes. All devices were stopped simultaneously at the completion of the run. Data collected across all devices includes average pace, best pace, average cadence, distance, ascent, and descent. The average percent difference and coefficient of variation (CV) between similar and different devices was calculated. RESULTS: The pairs of devices from the same manufacturer were found to be most consistent with each other (Garmin to Garmin: 3.27%; Polar to Polar: 1.4%; Stryd to Stryd: 1.15%) while devices from different manufacturers were found to be very different (Garmin to Polar: 12.75%; Garmin to Stryd: 10.11%; Polar to Stryd: 17.75%). Between devices from the same manufacturer, ascent was found to be least reliable (Garmin: CoV=0.20; Polar: CoV=0.12; Stryd: CoV=0.26). CONCLUSION: Data collected by wearable technologies of the same manufacturer will be mostly consistent with each other. However, data collected by a technology from a different manufacturer may be inconsistent with data from another device. In addition, elevation data may vary more than other data between watches. This finding is important because trail runners tend to compare their trail runs with other runners and often find ascent data important to measure progress. The location of the trail in a canyon may have impeded accuracy. Based on our findings, it may not be accurate to compare trail runs completed by runners with a different wearable technology device manufacturer