A sensitive method for the determination of amitriptyline and nortriptyline in human plasma

The kinetics of the male gametogenesis during the pregonadal period, prespermatogenesis, and "early" spermatogenesis has been described in detail. Concerning spermatogenesis in the adult individual reference is made to the articles of Courot, Hochereau-de Reviers and Ortavant (1970) and of Clermont (1972). The comparison of female and male gametogenesis (Fig. 1) shows that the "gonia stage" (asterisks) of the female germ cells is limited to one proliferation wave only, whereas the "gonia stage" of the male germ cells consists of a first proliferation wave, comparable to that of oogonia, a preparative phase to initiate spermatogenesis, and a second proliferation wave with renewal and differentiation of the spermatogonia. Germ cells in the "gonia stage" are highly sensitive towards ionising radiation and cytostatic drugs.     

Mixed mode fracture toughness of GFRP composites

Glass fibre reinforced polymer (GFRP) composites are used in a wide range of applications as a structural material. They have high specific mechanical properties but are prone to delamination as a result of manufacturing defects and impact/shock loading. The ability of the structure to continue to carry load after damage and the subsequent propensity of the damage to propagate are important considerations for the design of damage tolerant composite structures. In order to accurately predict the stability of damage under load, relevant mechanical properties of the material must be accurately determined. In particular, mixed mode fracture toughness data is required in order to study the damage criticality in such structures. This paper describes an experimental study to determine Mixed Mode fracture toughness for thick glass/vinylester specimens. The test methodology used for the experiments and its difficulties will be discussed. Mixed mode fracture toughness results are presented, as are Mode I and Mode II fracture toughness results obtained via Double Cantilever Beam (DCB) and End Notch Flexure (ENF) tests, respectively.     

A method for using legacy data for metamodel-based design of large-scale systems

Despite a steady increase in computing power, the complexity of engineering analyses seems to advance at the same rate. Traditional parametric design analysis is inadequate for the analysis of large-scale engineering systems because of its computational inefficiency; therefore, a departure from the traditional parametric design approach is required. In addition, the existence of legacy data for complex, large-scale systems is commonplace. Approximation techniques may be applied to build computationally inexpensive surrogate models for large-scale systems to replace expensive-to-run computer analysis codes or to develop a model for a set of nonuniform legacy data. Response-surface models are frequently utilized to construct surrogate approximations; however, they may be inefficient for systems having with a large number of design variables. Kriging, an alternative method for creating surrogate models, is applied in this work to construct approximations of legacy data for a large-scale system. Comparisons between response surfaces and kriging are made using the legacy data from the High Speed Civil Transport (HSCT) approximation challenge. Since the analysis points already exist, a modified design-of-experiments technique is needed to select the appropriate sample points. In this paper, a method to handle this problem is presented, and the results are compared against previous work.     

Self-disgust mediates the relationship between dysfunctional cognitions and depressive symptomatology.

Disgust has been linked to several psychopathologies, although a role in depression has been questioned. However, it has recently been proposed that rather than general disgust sensitivity, disgust directed toward the self (self-disgust) may influence the development of depression, providing a causal link between dysfunctional cognitions and depressive symptomatology. This possibility was examined by developing a scale to measure self-disgust (the Self-Disgust Scale; SDS) and then using mediator analysis to determine if self-disgust was able to explain the relationship between dysfunctional cognitions (measured with the use of the Dysfunctional Attitudes Scale) and depressive symptomatology (measured with the use of the Beck Depression Inventory and the Depression, Anxiety and Stress Scale). The developed SDS was found to exhibit a high level of internal consistency, test-retest reliability, and concurrent validity. Principal-components analysis revealed two factors to underlie responses to SDS items: the 'Disgusting self,' concerned with enduring, context independent aspects of the self, and 'Disgusting ways,' concerned with behavior. Self-disgust was found to mediate the relationship between dysfunctional cognitions and depressive symptomatology, demonstrating for the first time that self-disgust plays a role in depression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Identifying cell-to-cell variability in internalization using flow cytometry

Biological heterogeneity is a primary contributor to the variation observed in experiments that probe dynamical processes, such as the internalization of material by cells. Given that internalization is a critical process by which many therapeutics and viruses reach their intracellular site of action, quantifying cell-to-cell variability in internalization is of high biological interest. Yet, it is common for studies of internalization to neglect cell-to-cell variability. We develop a simple mathematical model of internalization that captures the dynamical behaviour, cell-to-cell variation, and extrinsic noise introduced by flow cytometry. We calibrate our model through a novel distribution-matching approximate Bayesian computation algorithm to flow cytometry data of internalization of anti-transferrin receptor antibody in a human B-cell lymphoblastoid cell line. This approach provides information relating to the region of the parameter space, and consequentially the nature of cell-to-cell variability, that produces model realizations consistent with the experimental data. Given that our approach is agnostic to sample size and signal-to-noise ratio, our modelling framework is broadly applicable to identify biological variability in single-cell data from internalization assays and similar experiments that probe cellular dynamical processes.     

Mixed-integer linear programming models for batch sterilization of packaged-foods plants

Batch sterilization with individual retorts is a common mode of operation in many food-canning plants. Although high-speed processing with continuous rotary or hydrostatic retort systems is used in very large canning factories, such systems are not economically feasible in the majority of small- to medium-sized canneries. In such canneries, sterilization is carried out in a battery of retorts as a batch process. Although the unloading and reloading operations for each retort are labor intensive, a well-designed and managed plant can operate with surprising efficiency if it has the optimum number of retorts and scheduling of retort operation. The objective of this research was to present two mathematical models for sterilization scheduling in food-canning plants. The first model developed is for the case where given amount of different canned food products with specific quality requirements would be sterilized within a minimum plant operation time in an autoclave of given capacity. The second model addresses the problem of maximizing the amount of sterilized products in an autoclave of given capacity for given plant operation time. The developed models were based on mixed-integer linear programming and incorporated the possibility of simultaneous sterilization. Simultaneous sterilization applies mainly to small canneries with few retorts. In these situations, retorts often operate with only partial loads because of the small lot sizes, and they are severely under-utilized. In order to demonstrate the feasibility of the mixed-integer linear programming (MILP) models, several examples involving the sterilization of different products were included in this research. The methodology proposed in this study is of special relevance for small- and medium-sized food-canning plants that normally work with many different products at the same time.     

Techniques for monitoring protein misfolding and aggregation in vitro and in living cells

Protein misfolding and aggregation have been considered important in understanding many neurodegenerative diseases and recombinant biopharmaceutical production. Various traditional and modern techniques have been utilized to monitor protein aggregation in vitro and in living cells. Fibril formation, morphology and secondary structure content of amyloidogenic proteins in vitro have been monitored by molecular probes, TEM/AFM, and CD/FTIR analyses, respectively. Protein aggregation in living cells has been qualitatively or quantitatively monitored by numerous molecular folding reporters based on either fluorescent protein or enzyme. Aggregation of a target protein is directly correlated to the changes in fluorescence or enzyme activity of the folding reporter fused to the target protein, which allows non-invasive monitoring aggregation of the target protein in living cells. Advances in the techniques used to monitor protein aggregation in vitro and in living cells have greatly facilitated the understanding of the molecular mechanism of amyloidogenic protein aggregation associated with neurodegenerative diseases, optimizing culture conditions to reduce aggregation of biopharmaceuticals expressed in living cells, and screening of small molecule libraries in the search for protein aggregation inhibitors.