Systematic Error Detection in Laboratory Medicine

Measurements in laboratory medicine have a degree of uncertainty; this uncertainty is often called “error” and refers to imprecisions and inaccuracies in measurement. This measurement error refers to the difference between the true value of the measured sample and the measured value. One of the types of error is systematic error, also called bias, because these errors errors are reproducible and skew the results consistently in the same direction. A common approach to identify systematic error is to use control samples with a method comparison approach. An alternative is use of statistical methods that analyze actual patient values either as an “Average of Normals” or a “Moving Patient Averages.” Fundamental questions should be decided before a quality control method is used: how are weights assigned to the results? Is preference given to more recent samples or to the older samples? How sensitive should the model be? In this chapter, we will expand the fundamental notion of systematic error and explain why it is difficult to identify and measure and current statistical methods that are used to detect systematic error or bias

Matching the Scales of Planning and Environmental Risk: an Evaluation of Community Wildfire Protection Plans in the Western US

Theory predicts that effective environmental governance requires that the scales of management account for the scales of environmental processes. A good example is community wildfire protection planning. Plan boundaries that are too narrowly defined may miss sources of wildfire risk originating at larger geographic scales whereas boundaries that are too broadly defined dilute resources. Although the concept of scale (mis)matches is widely discussed in literature on risk mitigation as well as environmental governance more generally, rarely has the concept been rigorously quantified. We introduce methods to address this limitation, and we apply our approach to assess scale matching among Community Wildfire Protection Plans (CWPPs) in the western US. Our approach compares two metrics: (1) the proportion of risk sources encompassed by planning jurisdictions (sensitivity) and (2) the proportion of area in planning jurisdictions in which risk can originate (precision). Using data from 852 CWPPs and a published library of 54 million simulated wildfires, we demonstrate a trade-off between sensitivity and precision. Our analysis reveals that spatial scale match—the product of sensitivity and precision—has an n-shaped relationship with jurisdiction size and is maximal at approximately 500 km2. Bayesian multilevel models further suggest that functional scale match—via neighboring, nested, and overlapping planning jurisdictions—may compensate for low sensitivity. This study provides a rare instance of a quantitative framework to measure scale match in environmental planning and has broad implications for risk mitigation as well as in other environmental governance settings

Global, cell non-autonomous gene regulation drives individual lifespan among isogenic C. elegans

Across species, lifespan is highly variable among individuals within a population. Even genetically identica

Poptosis or Peptide-Induced Transmembrane Pore Formation: A Novel Way to Kill Cancer Cells without Affecting Normal Cells

Recent advances in cancer treatment like personalized chemotherapy and immunotherapy are aimed at tumors that meet certain specifications. In this review, we describe a new approach to general cancer treatment, termed peptide-induced poptosis, in which specific peptides, e.g., PNC-27 and its shorter analogue, PNC-28, that contain the segment of the p53 transactivating 12-26 domain that bind to HDM-2 in its 1-109 domain, bind to HDM-2 in the membranes of cancer cells, resulting in transmembrane pore formation and the rapid extrusion of cancer cell contents, i.e., tumor cell necrosis. These peptides cause tumor cell necrosis of a wide variety of solid tissue and hematopoietic tumors but have no effect on the viability and growth of normal cells since they express at most low levels of membrane-bound HDM-2. They have been found to successfully treat a highly metastatic pancreatic tumor as well as stem-cell-enriched human acute myelogenous leukemias in nude mice, with no evidence of off-target effects. These peptides also are cytotoxic to chemotherapy-resistant cancers and to primary tumors. We performed high-resolution scanning immuno-electron microscopy and visualized the pores in cancer cells induced by PNC-27. This peptide forms 1:1 complexes with HDM-2 in a temperature-independent step, followed by dimerization of these complexes to form transmembrane channels in a highly temperature-dependent step parallel to the mode of action of other membranolytic but less specific agents like streptolysin. These peptides therefore may be effective as general anti-cancer agents

PNC-27, a Chimeric p53-Penetratin Peptide Binds to HDM-2 in a p53 Peptide-like Structure, Induces Selective Membrane-Pore Formation and Leads to Cancer Cell Lysis

PNC-27, a 32-residue peptide that contains an HDM-2 binding domain and a cell-penetrating peptide (CPP) leader sequence kills cancer, but not normal, cells by binding to HDM-2 associated with the plasma membrane and induces the formation of pores causing tumor cell lysis and necrosis. Conformational energy calculations on the structure of PNC-27 bound to HDM-2 suggest that 1:1 complexes form between PNC-27 and HDM-2 with the leader sequence pointing away from the complex. Immuno-scanning electron microscopy was carried out with cancer cells treated with PNC-27 and decorated with an anti-PNC-27 antibody coupled to 6 nm gold particles and an anti-HDM-2 antibody linked to 15 nm gold particles. We found multiple 6 nm- and 15 nm-labeled gold particles in approximately 1:1 ratios in layered ring-shaped structures in the pores near the cell surface suggesting that these complexes are important to the pore structure. No pores formed in the control, PNC-27-treated untransformed fibroblasts. Based on the theoretical and immuno-EM studies, we propose that the pores are lined by PNC-27 bound to HDM-2 at the membrane surface with the PNC-27 leader sequence lining the pores or by PNC-27 bound to HDM-2

Eukaryotic Evolutionary Transitions Are Associated with Extreme Codon Bias in Functionally-Related Proteins

Codon bias in the genome of an organism influences its phenome by changing the speed and efficiency of mRNA translation and hence protein abundance. We hypothesized that differences in codon bias, either between-species differences in orthologous genes, or within-species differences between genes, may play an evolutionary role. To explore this hypothesis, we compared the genome-wide codon bias in six species that occupy vital positions in the Eukaryotic Tree of Life. We acquired the entire protein coding sequences for these organisms, computed the codon bias for all genes in each organism and explored the output for relationships between codon bias and protein function, both within- and between-lineages. We discovered five notable coordinated patterns, with extreme codon bias most pronounced in traits considered highly characteristic of a given lineage. Firstly, the Homo sapiens genome had stronger codon bias for DNA-binding transcription factors than the Saccharomyces cerevisiae genome, whereas the opposite was true for ribosomal proteins – perhaps underscoring transcriptional regulation in the origin of complexity. Secondly, both mammalian species examined possessed extreme codon bias in genes relating to hair – a tissue unique to mammals. Thirdly, Arabidopsis thaliana showed extreme codon bias in genes implicated in cell wall formation and chloroplast function – which are unique to plants. Fourthly, Gallus gallus possessed strong codon bias in a subset of genes encoding mitochondrial proteins – perhaps reflecting the enhanced bioenergetic efficiency in birds that co-evolved with flight. And lastly, the G. gallus genome had extreme codon bias for the Ciliary Neurotrophic Factor – which may help to explain their spontaneous recovery from deafness. We propose that extreme codon bias in groups of genes that encode functionally related proteins has a pathway-level energetic explanation

Imaging the Impact of Chemically Inducible Proteins on Cellular Dynamics In Vivo

The analysis of dynamic events in the tumor microenvironment during cancer progression is limited by the complexity of current in vivo imaging models. This is coupled with an inability to rapidly modulate and visualize protein activity in real time and to understand the consequence of these perturbations in vivo. We developed an intravital imaging approach that allows the rapid induction and subsequent depletion of target protein levels within human cancer xenografts while assessing the impact on cell behavior and morphology in real time. A conditionally stabilized fluorescent E-cadherin chimera was expressed in metastatic breast cancer cells, and the impact of E-cadherin induction and depletion was visualized using real-time confocal microscopy in a xenograft avian embryo model. We demonstrate the assessment of protein localization, cell morphology and migration in cells undergoing epithelial-mesenchymal and mesenchymal-epithelial transitions in breast tumors. This technique allows for precise control over protein activity in vivo while permitting the temporal analysis of dynamic biophysical parameters

Foot-and-mouth disease virus 2C is a hexameric AAA+ protein with a coordinated ATP hydrolysis mechanism.

Foot-and-mouth disease virus (FMDV), a positive sense, single-stranded RNA virus, causes a highly contagious disease in cloven-hoofed livestock. Like other picornaviruses, FMDV has a conserved 2C protein assigned to the superfamily 3 helicases a group of AAA+ ATPases that has a predicted N-terminal membrane-binding amphipathic helix attached to the main ATPase domain. In infected cells, 2C is involved in the formation of membrane vesicles, where it co-localizes with viral RNA replication complexes, but its precise role in virus replication has not been elucidated. We show here that deletion of the predicted N-terminal amphipathic helix enables overexpression in Escherichia coli of a highly soluble truncated protein, 2C(34–318), that has ATPase and RNA binding activity. ATPase activity was abrogated by point mutations in the Walker A (K116A) and B (D160A) motifs and Motif C (N207A) in the active site. Unliganded 2C(34–318) exhibits concentration-dependent self-association to yield oligomeric forms, the largest of which is tetrameric. Strikingly, in the presence of ATP and RNA, FMDV 2C(34–318) containing the N207A mutation, which binds but does not hydrolyze ATP, was found to oligomerize specifically into hexamers. Visualization of FMDV 2C-ATP-RNA complexes by negative stain electron microscopy revealed hexameric ring structures with 6-fold symmetry that are characteristic of AAA+ ATPases. ATPase assays performed by mixing purified active and inactive 2C(34–318) subunits revealed a coordinated mechanism of ATP hydrolysis. Our results provide new insights into the structure and mechanism of picornavirus 2C proteins that will facilitate new investigations of their roles in infection

Effects of Macromolecular Crowding on Protein Conformational Changes

Many protein functions can be directly linked to conformational changes. Inside cells, the equilibria and transition rates between different conformations may be affected by macromolecular crowding. We have recently developed a new approach for modeling crowding effects, which enables an atomistic representation of “test” proteins. Here this approach is applied to study how crowding affects the equilibria and transition rates between open and closed conformations of seven proteins: yeast protein disulfide isomerase (yPDI), adenylate kinase (AdK), orotidine phosphate decarboxylase (ODCase), Trp repressor (TrpR), hemoglobin, DNA β-glucosyltransferase, and Ap4A hydrolase. For each protein, molecular dynamics simulations of the open and closed states are separately run. Representative open and closed conformations are then used to calculate the crowding-induced changes in chemical potential for the two states. The difference in chemical-potential change between the two states finally predicts the effects of crowding on the population ratio of the two states. Crowding is found to reduce the open population to various extents. In the presence of crowders with a 15 Å radius and occupying 35% of volume, the open-to-closed population ratios of yPDI, AdK, ODCase and TrpR are reduced by 79%, 78%, 62% and 55%, respectively. The reductions for the remaining three proteins are 20–44%. As expected, the four proteins experiencing the stronger crowding effects are those with larger conformational changes between open and closed states (e.g., as measured by the change in radius of gyration). Larger proteins also tend to experience stronger crowding effects than smaller ones [e.g., comparing yPDI (480 residues) and TrpR (98 residues)]. The potentials of mean force along the open-closed reaction coordinate of apo and ligand-bound ODCase are altered by crowding, suggesting that transition rates are also affected. These quantitative results and qualitative trends will serve as valuable guides for expected crowding effects on protein conformation changes inside cells