Systemic Control of Bone Homeostasis by FGF23 Signaling

The regulation of phosphate metabolism as an influence on bone homeostasis is profound. Recent advances in understanding the systemic control of Fibroblast growth factor-23 (FGF23) has uncovered novel effectors of endocrine feedback loops for calcium, phosphate, and vitamin D balance that interact with 'traditional' feedback loops for mineral metabolism. Not only are these findings re-shaping research studying phosphate handling and skeletal interactions, they have provided new therapeutic interventions. Emerging data support that the control of FGF23 production in bone and its circulating concentrations is a multi-layered process, with some influences affecting FGF23 transcription and some post-translational modification of the secreted, bioactive protein. Additionally, the actions of FGF23 on its target tissues via its co-receptor αKlotho, are subject to regulatory events just coming to light. The recent findings of systemic influences on circulating FGF23 and the downstream manifestations on bone homeostasis will be reviewed herein

Heritable and acquired disorders of phosphate metabolism: Etiologies involving FGF23 and current therapeutics

Phosphate is critical for many cellular processes and structural functions, including as a key molecule for nucleic acid synthesis and energy metabolism, as well as hydroxyapatite formation in bone. Therefore it is critical to maintain tight regulation of systemic phosphate levels. Based upon its broad biological importance, disruption of normal phosphate homeostasis has detrimental effects on skeletal integrity and overall health. Investigating heritable diseases of altered phosphate metabolism has led to key discoveries underlying the regulation and systemic actions of the phosphaturic hormone Fibroblast growth factor-23 (FGF23). Both molecular and clinical studies have revealed novel targets for the development and optimization of therapies for disorders of phosphate handling. This review will focus upon the bridge between genetic discoveries involving disorders of altered FGF23 bioactivity, as well as describe how these findings have translated into pharmacologic application

Emperical Tests of Acceptance Sampling Plans

Acceptance sampling is a quality control procedure applied as an alternative to 100% inspection. A random sample of items is drawn from a lot to determine the fraction of items which have a required quality characteristic. Both the number of items to be inspected and the criterion for determining conformance of the lot to the requirement are given by an appropriate sampling plan with specified risks of Type I and Type II sampling errors. In this paper, we present the results of empirical tests of the accuracy of selected sampling plans reported in the literature. These plans are for measureable quality characteristics which are known have either binomial, exponential, normal, gamma, Weibull, inverse Gaussian, or Poisson distributions. In the main, results support the accepted wisdom that variables acceptance plans are superior to attributes (binomial) acceptance plans, in the sense that these provide comparable protection against risks at reduced sampling cost. For the Gaussian and Weibull plans, however, there are ranges of the shape parameters for which the required sample sizes are in fact larger than the corresponding attributes plans, dramatically so for instances of large skew. Tests further confirm that the published inverse-Gaussian (IG) plan is flawed, as reported by White and Johnson (2011)

Probabilistic Requirements (Partial) Verification Methods Best Practices Improvement. Variables Acceptance Sampling Calculators: Empirical Testing

The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. In this paper, the results of empirical tests intended to assess the accuracy of acceptance sampling plan calculators implemented for six variable distributions are presented

Probabilistic Requirements (Partial) Verification Methods Best Practices Improvement. Variables Acceptance Sampling Calculators: Derivations and Verification of Plans

The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques. This recommended procedure would be used as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. This document contains the outcome of the assessment

Emotional Intelligence and Managerial Communication

Educational credentials and work experience are not enough to become an effective manager. In this article, we explore emotional intelligence (EI) and its effects on managerial communication. Our findings show continuous effort to improve your EI leads to enhanced communication skills, better team environments and increased productivity. The literature on EI from books, published scholarly articles, and blogs are used to frame our argument. We find that corporations need managers to understand EI and personality strategies to enhance their managerial communication effectiveness. Managers will be able to improve their EI skills if they adhere to our 3 key takeaways: 1) master the four EI factors, 2) maintain personal identity by strengthening relationships, and 3) enhance your communication skills with practice

Extracting Information from Adaptive Control Experiments

Optical control of chemical reactivity is achieved through the use of photonic reagents, that is, “shaped” ultrafast optical pulses created using a pulse shaper. It has been demonstrated in a number of molecular systems that these pulses can effectively guide the system into a desired final state. Effective pulses are often found through an experimental search involving thousands of individual measurements. An examination of the pulses tested in these experiments can reveal the pulse features responsible for control and also the underlying molecular dynamics. In this article we review attempts to extract information from optical control experiments using adaptive learning algorithms to search the available parameter space, and we discuss how these kinds of experiments can be used to achieve and understand multiphoton optical control.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91361/1/397_ftp.pd