A high-resolution map of human evolutionary constraint using 29 mammals.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease

Iterative development of visual control systems in a research vivarium.

The goal of this study was to test the hypothesis that reintroduction of Continuous Performance Improvement (CPI) methodology, a lean approach to management at Seattle Children's (Hospital, Research Institute, Foundation), would facilitate engagement of vivarium employees in the development and sustainment of a daily management system and a work-in-process board. Such engagement was implemented through reintroduction of aspects of the Toyota Production System. Iterations of a Work-In-Process Board were generated using Shewhart's Plan-Do-Check-Act process improvement cycle. Specific attention was given to the importance of detecting and preventing errors through assessment of the following 5 levels of quality: Level 1, customer inspects; Level 2, company inspects; Level 3, work unit inspects; Level 4, self-inspection; Level 5, mistake proofing. A functioning iteration of a Mouse Cage Work-In-Process Board was eventually established using electronic data entry, an improvement that increased the quality level from 1 to 3 while reducing wasteful steps, handoffs and queues. A visual workplace was realized via a daily management system that included a Work-In-Process Board, a problem solving board and two Heijunka boards. One Heijunka board tracked cage changing as a function of a biological kanban, which was validated via ammonia levels. A 17% reduction in cage changing frequency provided vivarium staff with additional time to support Institute researchers in their mutual goal of advancing cures for pediatric diseases. Cage washing metrics demonstrated an improvement in the flow continuum in which a traditional batch and queue push system was replaced with a supermarket-type pull system. Staff engagement during the improvement process was challenging and is discussed. The collective data indicate that the hypothesis was found to be true. The reintroduction of CPI into daily work in the vivarium is consistent with the 4P Model of the Toyota Way and selected Principles that guide implementation of the Toyota Production System

The A3 Problem Solving Report: A 10-Step Scientific Method to Execute Performance Improvements in an Academic Research Vivarium

<div><p>The purpose of this study was to illustrate the application of A3 Problem Solving Reports of the Toyota Production System to our research vivarium through the methodology of Continuous Performance Improvement, a lean approach to healthcare management at Seattle Children's (Hospital, Research Institute, Foundation). The Report format is described within the perspective of a 10-step scientific method designed to realize measurable improvements of Issues identified by the Report's Author, Sponsor and Coach. The 10-step method (Issue, Background, Current Condition, Goal, Root Cause, Target Condition, Countermeasures, Implementation Plan, Test, and Follow-up) was shown to align with Shewhart's Plan-Do-Check-Act process improvement cycle in a manner that allowed for quantitative analysis of the Countermeasure's outcomes and of Testing results. During fiscal year 2012, 9 A3 Problem Solving Reports were completed in the vivarium under the teaching and coaching system implemented by the Research Institute. Two of the 9 reports are described herein. Report #1 addressed the issue of the vivarium's veterinarian not being able to provide input into sick animal cases during the work day, while report #7 tackled the lack of a standard in keeping track of weekend/holiday animal health inspections. In each Report, a measurable Goal that established the basis for improvement recognition was present. A Five Whys analysis identified the Root Cause for Report #1 as historical work patterns that existed before the veterinarian was hired on and that modern electronic communication tools had not been implemented. The same analysis identified the Root Cause for Report #7 as the vivarium had never standardized the process for weekend/holiday checks. Successful outcomes for both Reports were obtained and validated by robust audit plans. The collective data indicate that vivarium staff acquired a disciplined way of reporting on, as well as solving, problems in a manner consistent with high level A3 Thinking.</p></div

A3 Problem Solving Reports in the Office of Animal Care during fiscal year 2012.

<p>A3 Problem Solving Reports in the Office of Animal Care during fiscal year 2012.</p

Levels of quality for A3 Report #1: DVM input within 2 hr of sick animal detection.

1<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076833#pone-0076833-t001" target="_blank">Table 1</a>.</p>2<p>N/A, not applicable.</p>3<p>company is Seattle Children's Research Institute.</p>4<p>work unit is the OAC.</p

Flow Continuum Categories.¹

1<p>Abstracted, with permission, from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090076#pone-0090076-g005" target="_blank">Figure 5</a>–11 of reference <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090076#pone.0090076-Liker7" target="_blank">[15]</a>.</p

Current and Target Conditions for A3 Report “Veterinarian input into treatment of sick animals”.

<p>Animal cases are classified as either “urgent” or “sick” and are typically first detected by one of six animal technicians (AT). In each case, a single veterinary technician (VT) provides the primary interface to the researchers (PI, lab).</p

Various types of visual controls in production processes.

1<p>Based on fecal and urine pattern in the dirty bedding of a mouse cage, the term <i>biological kanban</i> was originally coined by Khan and Umrysh (2008) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090076#pone.0090076-Khan1" target="_blank">[23]</a>. The data presented in Results section V (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090076#pone-0090076-g005" target="_blank">Figure 5B</a>) strengthens this term by relating ammonia levels to fecal/urine patterns – thus signaling to staff that it is time to change the cage.</p>2<p>For a more detailed discussion of pitch, and how it relates to takt time, the reader is referred to <i>Creating a Lean Culture</i> by David Mann <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090076#pone.0090076-Mann2" target="_blank">[42]</a>.</p

Baseline and follow up metrics for A3 Report #1: DVM input into treatment of sick animals.

1<p>AT, animal technician; VT, veterinary technician.</p>2<p>N/A, not applicable.</p