Morphology and fracture of enamel

This study examines the inter-relation between enamel morphology and crack resistance by sectioning extracted human molars after loading to fracture. Cracks appear to initiate from tufts, hypocalcified defects at the enamel–dentin junction, and grow longitudinally around the enamel coat to produce failure. Microindentation corner cracks placed next to the tufts in the sections deflect along the tuft interfaces and occasionally penetrate into the adjacent enamel. Although they constitute weak interfaces, the tufts are nevertheless filled with organic matter, and appear to be stabilized against easy extension by self-healing, as well as by mutual stress-shielding and decussation, accounting at least in part for the capacity of tooth enamel to survive high functional forces.

Properties of tooth enamel in great apes

A comparative study has been made of human and great ape molar tooth enamel. Nanoindentation techniques are used to map profiles of elastic modulus and hardness across sections from the enamel–dentin junction to the outer tooth surface. The measured data profiles overlap between species, suggesting a degree of commonality in material properties. Using established deformation and fracture relations, critical loads to produce function-threatening damage in the enamel of each species are calculated for characteristic tooth sizes and enamel thicknesses. The results suggest that differences in load-bearing capacity of molar teeth in primates are less a function of underlying material properties than of morphology.

A systems analysis identifies a feedforward inflammatory circuit leading to lethal influenza infection

For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium versus dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis, together with these gene expression and flow data, identified a chemokine-driven feedforward circuit involving proinflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation, but not ablation, of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology.

Application of Cognitive Engineering Principles to the Redesign of a Dichotomous Identification Key for Parasitology

Dichotomous identification keys are used throughout biology for identification of plants, insects, and parasites. However, correct use of identification keys can be difficult as they are not usually intended for novice users who may not be familiar with the terminology used or with the morphology of the organism being identified. Therefore, we applied cognitive engineering principles to redesign a parasitology identification key for the Internet. We addressed issues of visual clutter and spatial distance by displaying a single question couplet at a time and by switching to the appropriate next couplet after the user made a choice. Our analysis of the original paper-based key versus the Web-based approach found that of 26 applicable cognitive engineering principles, the paper key did not meet 4 (15%) and partially met 11 (42%). In contrast, the redesigned key met 100% of 32 applicable cognitive engineering principles.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

NEW TARGET GENES FOR TUMOR SUPPRESSORS p53 AND p73 IN REGENERATING LIVER

The p53-family of proteins regulates expression of target genes during tissue development and differentiation. Within the p53-family, p53 and p73 have hepatic-specific functions in development and tumor suppression. Despite a growing list of p53/p73 target genes, very few of these have been studied in vivo, and the knowledge regarding functions of p53 and p73 in normal tissues remains limited. p53+/-p73+/- mice develop hepatocellular carcinoma (HCC), whereas overexpression of p53 in human HCC leads to tumor regression. However, the mechanism of p53/p73 function in liver remains poorly characterized. Here, the model of mouse liver regeneration is used to identify new target genes for p53/p73 in normal quiescent vs. proliferating cells. In response to surgical removal of ~2/3 of liver mass (partial hepatectomy, PH), the remaining hepatocytes exit G0 of cell cycle and undergo proliferation to reestablish liver mass. The hypothesis tested in this work is that p53/p73 functions in cell cycle arrest, apoptosis and senescence are repressed during liver regeneration, and reactivated at the end of the regenerative response. Chromatin immunoprecipitation (ChIP), with a p73-antibody, was used to probe arrayed genomic sequences (ChIP-chip) and uncover 158 potential targets of p73-regulation in normal liver. Global microarray analysis of mRNA levels, at T=0-48h following PH, revealed sets of genes that change expression during regeneration. Eighteen p73-bound genes changed expression after PH. Four of these genes, Foxo3, Jak1, Pea15, and Tuba1 have p53 response elements (p53REs), identified in silico within the upstream regulatory region. Forkhead transcription factor Foxo3 is the most responsive gene among transcription factors with altered expression during regenerative, cellular proliferation. p53 and p73 bind a Foxo3 p53RE and maintain active expression in quiescent liver. During liver regeneration, binding of p53 and p73, recruitment of acetyltransferase p300, and an active chromatin structure of Foxo3 are disrupted, alongside loss of Foxo3 expression. These parameters of Foxo3 regulation are reestablished at completion of liver growth and regeneration, supporting a temporary suspension of p53 and p73 regulatory functions in normal cells during tissue regeneration.

Myogenin modulates exercise endurance by altering skeletal muscle metabolism

The function of myogenic regulatory factors (MRFs) during adult life is not well understood. The requirement of one of these MRFs, myogenin (Myog), during embryonic muscle development suggests an equally important role in adult muscle. In this study, we have determined the function of myogenin during adult life using a conditional allele of Myog. In contrast to embryonic development, myogenin is not required for adult viability, and Myog-deleted mice exhibited no remarkable phenotypic changes during sedentary life. Remarkably, sedentary Myog-deleted mice demonstrated enhanced exercise endurance during involuntary treadmill running. Altered blood glucose and lactate levels in sedentary Myog-deleted mice after exhaustion suggest an enhanced glycolytic metabolism and an ability to excessively deplete muscle and liver glycogen stores. Traditional changes associated with enhanced exercise endurance, such as fiber type switching, and increased oxidative potential, were not detected in sedentary Myog-deleted mice. After long-term voluntary exercise, trained Myog-deleted mice demonstrated an enhanced adaptive response to exercise. Trained Myog-deleted mice exhibited superior exercise endurance associated with an increased proportion of slow-twitch fibers and increased oxidative capacity. In a parallel experiment, dystrophin-deficient young adult mice showed attenuated muscle fatigue following the deletion of Myog. These results demonstrate a novel and unexpected role for myogenin in modulating skeletal muscle metabolism.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Hebbian analysis of the transformation of medial entorhinal grid-cell inputs to hippocampal place fields.

The discovery of grid cells in the medial entorhinal cortex (MEC) permits the characterization of hippocampal computation in much greater detail than previously possible. The present study addresses how an integrate-and-fire unit driven by grid-cell spike trains may transform the multipeaked, spatial firing pattern of grid cells into the single-peaked activity that is typical of hippocampal place cells. Previous studies have shown that in the absence of network interactions, this transformation can succeed only if the place cell receives inputs from grids with overlapping vertices at the location of the place cell's firing field. In our simulations, the selection of these inputs was accomplished by fast Hebbian plasticity alone. The resulting nonlinear process was acutely sensitive to small input variations. Simulations differing only in the exact spike timing of grid cells produced different field locations for the same place cells. Place fields became concentrated in areas that correlated with the initial trajectory of the animal; the introduction of feedback inhibitory cells reduced this bias. These results suggest distinct roles for plasticity of the perforant path synapses and for competition via feedback inhibition in the formation of place fields in a novel environment. Furthermore, they imply that variability in MEC spiking patterns or in the rat's trajectory is sufficient for generating a distinct population code in a novel environment and suggest that recalling this code in a familiar environment involves additional inputs and/or a different mode of operation of the network.

Cellular dynamic simulator: an event driven molecular simulation environment for cellular physiology.

In this paper, we present the Cellular Dynamic Simulator (CDS) for simulating diffusion and chemical reactions within crowded molecular environments. CDS is based on a novel event driven algorithm specifically designed for precise calculation of the timing of collisions, reactions and other events for each individual molecule in the environment. Generic mesh based compartments allow the creation / importation of very simple or detailed cellular structures that exist in a 3D environment. Multiple levels of compartments and static obstacles can be used to create a dense environment to mimic cellular boundaries and the intracellular space. The CDS algorithm takes into account volume exclusion and molecular crowding that may impact signaling cascades in small sub-cellular compartments such as dendritic spines. With the CDS, we can simulate simple enzyme reactions; aggregation, channel transport, as well as highly complicated chemical reaction networks of both freely diffusing and membrane bound multi-protein complexes. Components of the CDS are generally defined such that the simulator can be applied to a wide range of environments in terms of scale and level of detail. Through an initialization GUI, a simple simulation environment can be created and populated within minutes yet is powerful enough to design complex 3D cellular architecture. The initialization tool allows visual confirmation of the environment construction prior to execution by the simulator. This paper describes the CDS algorithm, design implementation, and provides an overview of the types of features available and the utility of those features are highlighted in demonstrations.

Characterization of Hsp70 binding and nucleotide exchange by the yeast Hsp110 chaperone Sse1.

SSE1 and SSE2 encode the essential yeast members of the Hsp70-related Hsp110 molecular chaperone family. Both mammalian Hsp110 and the Sse proteins functionally interact with cognate cytosolic Hsp70s as nucleotide exchange factors. We demonstrate here that Sse1 forms high-affinity (Kd approximately 10-8 M) heterodimeric complexes with both yeast Ssa and mammalian Hsp70 chaperones and that binding of ATP to Sse1 is required for binding to Hsp70s. Sse1.Hsp70 heterodimerization confers resistance to exogenously added protease, indicative of conformational changes in Sse1 resulting in a more compact structure. The nucleotide binding domains of both Sse1/2 and the Hsp70s dictate interaction specificity and are sufficient for mediating heterodimerization with no discernible contribution from the peptide binding domains. In support of a strongly conserved functional interaction between Hsp110 and Hsp70, Sse1 is shown to associate with and promote nucleotide exchange on human Hsp70. Nucleotide exchange activity by Sse1 is physiologically significant, as deletion of both SSE1 and the Ssa ATPase stimulatory protein YDJ1 is synthetically lethal. The Hsp110 family must therefore be considered an essential component of Hsp70 chaperone biology in the eukaryotic cell.

Dominance of the proximal coordinate frame in determining the locations of hippocampal place cell activity during navigation.

The place-specific activity of hippocampal cells provides downstream structures with information regarding an animal's position within an environment and, perhaps, the location of goals within that environment. In rodents, recent research has suggested that distal cues primarily set the orientation of the spatial representation, whereas the boundaries of the behavioral apparatus determine the locations of place activity. The current study was designed to address possible biases in some previous research that may have minimized the likelihood of observing place activity bound to distal cues. Hippocampal single-unit activity was recorded from six freely moving rats as they were trained to perform a tone-initiated place-preference task on an open-field platform. To investigate whether place activity was bound to the room- or platform-based coordinate frame (or both), the platform was translated within the room at an "early" and at a "late" phase of task acquisition (Shift 1 and Shift 2). At both time points, CA1 and CA3 place cells demonstrated room-associated and/or platform-associated activity, or remapped in response to the platform shift. Shift 1 revealed place activity that reflected an interaction between a dominant platform-based (proximal) coordinate frame and a weaker room-based (distal) frame because many CA1 and CA3 place fields shifted to a location intermediate to the two reference frames. Shift 2 resulted in place activity that became more strongly bound to either the platform- or room-based coordinate frame, suggesting the emergence of two independent spatial frames of reference (with many more cells participating in platform-based than in room-based representations).

ROLE OF PROSTAGLANDIN E2 IN THE REGULATION OF PANCREATIC STELLATE CELLS HYPER ACTIVITY ASSOCIATED WITH PANCREATIC CANCER

Pancreatic cancer is one of the most lethal type of cancer due to its high metastasis rate and resistance to chemotherapy. Pancreatic fibrosis is a constant pathological feature of chronic pancreatitis and the hyperactive stroma associated with pancreatic cancer. Strong evidence supports an important role of cyclooxygenase-2 (COX-2) and COX-2 generated prostaglandin E2 (PGE2) during pancreatic fibrosis. Pancreatic stellate cells (PSC) are the predominant source of extracellular matrix production (ECM), thus being the key players in both diseases. Given this background, the primary objective is to delineate the role of PGE2 on human pancreatic stellate cells (PSC) hyper activation associated with pancreatic cancer. This study showed that human PSC cells express COX-2 and synthesize high levels of PGE2. PGE2 stimulated PSC migration and invasion; expression of extra cellular matrix (ECM) genes and tissue degrading matrix metallo proteinases (MMP) genes. I further identified the PGE2 EP receptor responsible for mediating these effects on PSC. Using genetic and pharmacological approaches I identified the receptor required for PGE2 mediates PSC hyper activation. Treating PSC with Specific antagonists against EP1, EP2 and EP4, demonstrated that blocking EP4 receptor only, resulted in a complete reduction of PGE2 mediated PSC activation. Furthermore, siRNA mediated silencing of EP4, but not other EP receptors, blocked the effects of PGE2 on PSC fibrogenic activity. Further examination of the downstream pathway modulators revealed that PGE2 stimulation of PSC involved CREB and not AKT pathway. The regulation of PSC by PGE2 was further investigated at the molecular level, with a focus on COL1A1. Collagen I deposition by PSC is one of the most important events in pancreatic cancer. I found that PGE2 regulates PSC through activation of COL1A1 expression and transcriptional activity. Downstream of PGE2, silencing of EP4 receptor caused a complete reduction of COL1A1 expression and activity supporting the role of EP4 mediated stimulation of PSC. Taken together, this data indicate that PGE2 regulates PSC via EP4 and suggest that EP4 can be a better therapeutic target for pancreatic cancer to reduce the extensive stromal reaction, possibly in combination with chemotherapeutic drugs can further kill pancreatic cancer cells.

Mechanical and Chemical Stability of Injection-Molded Microcantilevers Used for Sensing

Ultraviolet-ozone treatment is used as a standard surface cleaning procedure for removal of molecular organic contamination from analytical and sensing devices. Here, it is applied for injection-molded polymer microcantilevers before characterization and sensing experiments. This article examines the effects of the surface cleaning process using commercial equipment, in particular on the performance and mechanical properties of the cantilevers. It can be shown that the first chemical aging process essentially consist of the cross linking of the polymer chains together with a physical aging of the material. For longer exposure, the expected thermo-oxidative formation of carbonyl groups sets in and an exposure dependent chemical degradation can be detected. A process time of 20 min was found suitable as a trade-off between cleaning and stability