Gene therapy by intramuscular injection of plasmid DNA: studies on firefly luciferase gene expression in mice

Direct injection of nonviral, covalently closed circular plasmid DNA into muscle results in expression of the DNA in myofiber cells. We have examined the expression of firefly luciferase DNA constructs injected into adult murine skeletal muscle. Considerable variation in luciferase enzyme expression was noted among constructs with different regulatory elements, among different batches of the same DNA construct, and among similar transfection experiments performed at different times. This variation was minimized by using single batches of plasmid DNA and by performing comparable sets of experiments concurrently. A quantitative experimental protocol was defined for comparing various aspects of the transfection process. We report that a luciferase construct containing the human cytomegalovirus immediate-early gene promoter plus intron A (a construct termed "p-CMVint-lux") showed the highest expression among several constructs tested. Dose-response and time course analyses of p-CMVint-lux DNA injections showed that maximal luciferase expression was achieved with 25 micrograms of DNA at 7-14 days post-injection. Selected manipulations of the transfection process were examined for their influence on luciferase expression. Variations in the rate of DNA injection, needle size, injection volume, and vehicle temperature had no significant effect on luciferase expression. The presence of endotoxin, cationic peptide, muscle stimulants or relaxants, vasoconstrictors, metal chelators, or lysosomal lytic reagents had no significant effect on expression. However, linearization of the DNA, injection of the DNA in water rather than saline, or inclusion of a DNA intercalating agent nearly abolished luciferase expression. And finally, increasing the injection dose by giving multiple injections over a 10-day period increased expression proportionally to the number of injections.

Comparison of antibody functionality using different immobilization methods

This study investigates the influence of antibody immobilization methods on antigen capture. Adsorption and two surface chemistries, an aminosilane chemistry and a common heterobifunctional crosslinker (N-gamma-maleimidobutyryloxy-succinimide ester, GMBS), were compared and evaluated for their ability to immobilize antibodies and capture antigen. The role of protein A as an orienting protein scaffold component in each of these techniques was also evaluated. Through experimentation it was determined that the GMBS technique immobilized the highest amount of antibody and minimized nonspecific binding. For all techniques, the most functional antibodies were found to be those immobilized with protein A. Interestingly, the aminosilane technique demonstrated the highest antigen capture with antibody alone but also exhibited the highest level of nonspecific binding.

Comparative study of parameter sensitivity analyses of the TCR-activated Erk-MAPK signalling pathway

Parameter estimation is a major challenge for mathematical modelling of biological systems. Given the uncertainties associated with model parameters, it is important to understand how sensitive the model output is to variations in parameter values. A local sensitivity analysis determines the model sensitivity to parameter variations over a localised region around the nominal parameter values, whereas a global sensitivity analysis (GSA) investigates the sensitivity over the entire parameter space. Using a T-cell receptor-activated Erk-MAPK signalling pathway model as an example, the authors present a comparative study of a variety of different sensitivity analysis techniques. These techniques include: local sensitivity analysis, existing GSA methods of partial rank correlation coefficient, Sobol's, extended Fourier amplitude sensitivity test, as well as a weighted average of local sensitivities and a new GSA method to extract global parameter sensitivities from a parameter identification routine. Results of this study revealed critical reactions in the signalling pathway and their impact on the signalling dynamics and provided insights into embedded regulatory mechanisms such as feedback loops in the pathway. From this study, a recommendation emerges for a general sensitivity analysis strategy to efficiently and reliably infer quantitative, dynamic as well as topological properties from systems biology models.

Antisense RNA to the c-fos gene: restoration of density-dependent growth arrest in a transformed cell line

Fibroblasts transformed by v-sis have elevated levels of c-fos relative to non-transformed controls. Transfection and integration of plasmids directing the synthesis of antisense RNA to the c-fos gene leads to restoration of density-dependent growth arrest in monolayer culture, but does not inhibit colony formation in soft agar.

A new cardiopulmonary resuscitation method using only rhythmic abdominal compression

This article introduces 2 new cardiopulmonary resuscitation (CPR) concepts: (1) the use of only rhythmic abdominal compression (OAC) to produce blood flow during CPR with ventricular fibrillation and (2) a new way of describing coronary perfusion effectiveness, namely, the area between the aortic and right atrial pressure curves, summed over 1 minute, the units being millimeters of mercury per second. We call this unit the coronary perfusion index (CPI). True mean coronary perfusion pressure is CPI/60. We also relate CPI during CPR with ventricular fibrillation to the CPI for the normally beating heart in the same animal, obtained before each experiment. This 11-pig (25-35 kg) study compares the CPI for standard chest-compression CPR and that obtained with OAC-CPR. The coronary perfusion ratio for OAC-CPR compared with standard chest-compression CPR was 1.6 +/- 0.73 (P = .024). In other words, OAC-CPR produced 60% more coronary perfusion than standard chest-compression CPR, with no damage to visceral organs.

The humoral immune response to Haemophilus influenzae type b: a mathematical model based on T-zone and germinal center B-cell dynamics

Through careful mapping of the physiology of the T-zone and GC B-blast dynamics to a mathematical representation of the cell processes including proliferation, migration, differentiation, and cell death, a mathematical model is constructed to capture the dominant nominal primary, late follicular, and secondary humoral response to Haemophilus influenzae Type b. This model explicitly incorporates the dynamics of memory B-cells, T-zone and GC B-dynamics, IgM and IgG antibodies, avidity maturation, and IC presentation by FDCs into a coherent framework. This paper describes the relevant immunology, the pertinent physiological assumptions, the developed model, and the parameter identification procedure. The model parameters were found using a parameter identification procedure that capitalizes on the timing and interactions of certain dominant physiological attributes. Simulation results and validation tests indicate that the model reflects not only a nominal primary and secondary humoral immune response but also the tertiary and T-independent responses. The model shows robustness to variations in infection dosage, bacterial growth rate (virulence of the strain), and onset-timing of the secondary response. The utility of this model in studying the humoral immune response is demonstrated through suggested physiological assumptions, mechanisms, and rates to be eventually clinically evaluated as well as insights into vaccination design. The model and parameter identification techniques are easily adapted to other diseases which primarily evoke a humoral immune response.

How much lung ventilation is obtained with only chest-compression CPR?

The objective of this 14-pig study was designed to determine the amount of lung ventilation obtainable by only rhythmic chest compression (100/min, 100 lbs). Tidal volume (TV), dead space (DS), and respiration rate (R) were measured with normal breathing and with rhythmic chest compression during ventricular fibrillation. The ratio of TV/DS was calculated in both cases. For normal breathing the ratio was 2.54 +/- 0.68; for chest compression breathing the ratio was 0.80 +/- 0.07. Minute alveolar ventilation (TV - DS)R was computed for both cases. With spontaneous breathing, the minute alveolar volume was 5.48 +/- 2.1 l/min. With only chest-compression breathing, the alveolar ventilation was -1.49 +/- 0.64 l/min. The negative minute alveolar volume and fractional ratio reveals that TV was less than the dead space indicating that chest-compression alone does not ventilate the lungs.

Analysis of resonance chemotherapy in leukemia treatment via multi-staged population balance models

An age-structured population balance model that explicitly models cell cycle phases is developed to investigate the effects of cell cycle specific (CCS) drugs. In particular, the benefits of timing CCS drug treatments in resonance chemotherapy are predicted and measured directly in vitro before evaluating likely in vivo scenarios. The phase transition rates are measured in vitro for the HL60 leukemia cell line and are used to predict the transient phase dynamics after exposure to the S phase specific drug, camptothecin. The phase oscillations predicted by the model are observed experimentally and the timing of a second camptothecin pulse is shown to significantly alter the overall treatment effectiveness. To explore the feasibility of designing resonance chemotherapeutic treatments to preferentially eliminate one cell type over another, Jurkat and HL60 leukemia cells are exposed to the same dual-pulse camptothecin treatment regimen. With the model framework validated for simplified cases, the model is used to extrapolate the effectiveness of resonance chemotherapy considering in vivo effects such as quiescence, drug metabolism, drug properties, and transport considerations that were not included in the in vitro experiments. While resonance chemotherapy is intuitive and looks promising in vitro, when in vivo considerations are included in the model, the phenomenon is dampened and the window of applicability becomes narrower.

Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization

6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP's widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient's ability to metabolize the drug instead of the traditional standard-dose-for-all approach.

Biosensor immunosurface engineering inspired by B-cell membrane-bound antibodies: modeling and analysis of multivalent antigen capture by immobilized antibodies

Immobilized antibodies are used by many biosensors and diagnostic tests as specific receptors for the presence of targeted substances in clinical, biological, or environmental samples. The antibodies used in these devices are the soluble form of the antibodies presented on the B-cell membrane: they have the same specificity, but they may differ from those presented on the B cell in orientation, flexibility, mobility, and support-membrane properties. These properties influence the formation of noncovalent bonds between the pathogen antigenic determinants (epitopes) and the amino acids of the antibodies. This paper extends the theoretical modeling foundation addressing multivalent antigen binding to cell surface receptors to account for local and far-field antibody surface density effects, immobilized antibodies, and the flexibility and range of motion of immobilized antibodies. An analysis of the derived model provides insight into the design of biosensor immunosurfaces to enhance pathogen capture capability.

Estimation of likely cancer cure using first- and second-order product densities of population balance models

The objective of chemotherapy is to eradicate all cancerous cells. However, due to the stochastic behavior of cells, the elimination of all cancerous cells must be discussed probabilistically. We hypothesize, and demonstrate in the results, that the mean and standard deviation of a cancer cell population, derived through the probabilistic interpretation of population balance equations, are sufficient to estimate the likelihood of cancer eradication. Our analysis of a binary cell division model reveals that an expected cancer population that is six standard deviations less than one cell provides a good estimate for the treatment durations that nearly ensures treatment successes. This approximation is evaluated and tested on two other physiologically likely scenarios: variable patient response to chemotherapy and the presence of a dormant population. We find that early identification of individual patient susceptibility to the chemotherapeutic agent is extremely important to all patients as treatment adjustments for non-responders greatly enhances their likelihood of cure while responders need not be subjected to needlessly harsh treatments. Presence of a dormant population increases both the required treatment duration and population variability, but the same estimation method holds. This work is a step toward using stochastic models for a quantitative evaluation of chemotherapy.