A critical role for the T cell receptor alpha-chain connecting peptide domain in positive selection of CD1-independent NKT cells.

Natural killer T (NKT) cells are a subset of mature alpha beta TCR(+) cells that co-express NK lineage markers. Whereas most NKT cells express a canonical Valpha14/Vbeta8.2 TCR and are selected by CD1d, a minority of NKT cells express a diverse TCR repertoire and develop independently of CD1d. Little is known about the selection requirements of CD1d-independent NKT cells. We show here that NKT cells develop in RAG-deficient mice expressing an MHC class II-restricted transgenic TCR (Valpha2/Vbeta8.1) but only under conditions that lead to negative selection of conventional T cells. Moreover development of NKT cells in these mice is absolutely dependent upon an intact TCR alpha-chain connecting peptide domain, which is required for positive selection of conventional T cells via recruitment of the ERK signaling pathway. Collectively our data demonstrate that NKT cells can develop as a result of high avidity TCR/MHC class II interactions and suggest that common signaling pathways are involved in the positive selection of CD1d-independent NKT cells and conventional T cells.

Quantitative real-time polymerase chain reaction for detection of adenovirus after T cell-replete hematopoietic cell transplantation: viral load as a marker for invasive disease.

BACKGROUND: The value of adenovirus plasma DNA detection as an indicator for adenovirus disease is unknown in the context of T cell-replete hematopoietic cell transplantation, of which adenovirus disease is an uncommon but serious complication. METHODS: Three groups of 62 T cell-replete hematopoietic cell transplant recipients were selected and tested for adenovirus in plasma by polymerase chain reaction. RESULTS: Adenovirus was detected in 21 (87.5%) of 24 patients with proven adenovirus disease (group 1), in 4 (21%) of 19 patients who shed adenovirus (group 2), and in 1 (10.5%) of 19 uninfected control patients. The maximum viral load was significantly higher in group 1 (median maximum viral load, 6.3x10(6) copies/mL; range, 0 to 1.0x10(9) copies/mL) than in group 2 (median maximum viral load, 0 copies/mL; range, 0 to 1.7x10(8) copies/mL; P<.001) and in group 3 (median maximum viral load, 0 copies/mL; range 0-40 copies/mL; P<.001). All patients in group 2 who developed adenoviremia had symptoms compatible with adenovirus disease (i.e., possible disease). A minimal plasma viral load of 10(3) copies/mL was detected in all patients with proven or possible disease. Adenoviremia was detectable at a median of 19.5 days (range, 8-48 days) and 24 days (range, 9-41 days) before death for patients with proven and possible adenovirus disease, respectively. CONCLUSION: Sustained or high-level adenoviremia appears to be a specific and sensitive indicator of adenovirus disease after T cell-replete hematopoietic cell transplantation. In the context of low prevalence of adenovirus disease, the use of polymerase chain reaction of plasma specimens to detect virus might be a valuable tool to identify and treat patients at risk for viral invasive disease.

Two monoclonal rat antibodies with specificity for the beta-chain variable region V beta 6 of the murine T-cell receptor.

Two rat monoclonal antibodies (mAbs), 44-22-1 and 46-6B5, which recognize an alloreactive cytotoxic clone, 3F9, have been further tested on a panel of T hybridomas and cytotoxic T-cell clones for binding and functional activities. The mAbs recognized only those cells sharing the expression of the T-cell receptor beta-chain variable region gene V beta 6 with 3F9. All V beta 6+ cells were activated by these mAbs under cross-linking conditions and their antigen-specific activation was blocked by soluble mAb. Furthermore, depletion of 46-6B5+ normal lymph node T cells eliminated all cells expressing the epitope recognized by 44-22-1 and V beta 6 mRNA.

Stochastic time-concentration activity models for cytotoxicity in 3D brain cell cultures.

BACKGROUND: In vitro aggregating brain cell cultures containing all types of brain cells have been shown to be useful for neurotoxicological investigations. The cultures are used for the detection of nervous system-specific effects of compounds by measuring multiple endpoints, including changes in enzyme activities. Concentration-dependent neurotoxicity is determined at several time points. METHODS: A Markov model was set up to describe the dynamics of brain cell populations exposed to potentially neurotoxic compounds. Brain cells were assumed to be either in a healthy or stressed state, with only stressed cells being susceptible to cell death. Cells may have switched between these states or died with concentration-dependent transition rates. Since cell numbers were not directly measurable, intracellular lactate dehydrogenase (LDH) activity was used as a surrogate. Assuming that changes in cell numbers are proportional to changes in intracellular LDH activity, stochastic enzyme activity models were derived. Maximum likelihood and least squares regression techniques were applied for estimation of the transition rates. Likelihood ratio tests were performed to test hypotheses about the transition rates. Simulation studies were used to investigate the performance of the transition rate estimators and to analyze the error rates of the likelihood ratio tests. The stochastic time-concentration activity model was applied to intracellular LDH activity measurements after 7 and 14 days of continuous exposure to propofol. The model describes transitions from healthy to stressed cells and from stressed cells to death. RESULTS: The model predicted that propofol would affect stressed cells more than healthy cells. Increasing propofol concentration from 10 to 100 μM reduced the mean waiting time for transition to the stressed state by 50%, from 14 to 7 days, whereas the mean duration to cellular death reduced more dramatically from 2.7 days to 6.5 hours. CONCLUSION: The proposed stochastic modeling approach can be used to discriminate between different biological hypotheses regarding the effect of a compound on the transition rates. The effects of different compounds on the transition rate estimates can be quantitatively compared. Data can be extrapolated at late measurement time points to investigate whether costs and time-consuming long-term experiments could possibly be eliminated.

Population pharmacokinetic modelling and evaluation of different dosage regimens for darunavir and ritonavir in HIV-infected individuals.

OBJECTIVES: Darunavir is a protease inhibitor that is administered with low-dose ritonavir to enhance its bioavailability. It is prescribed at standard dosage regimens of 600/100 mg twice daily in treatment-experienced patients and 800/100 mg once daily in naive patients. A population pharmacokinetic approach was used to characterize the pharmacokinetics of both drugs and their interaction in a cohort of unselected patients and to compare darunavir exposure expected under alternative dosage regimens. METHODS: The study population included 105 HIV-infected individuals who provided darunavir and ritonavir plasma concentrations. Firstly, a population pharmacokinetic analysis for darunavir and ritonavir was conducted, with inclusion of patients' demographic, clinical and genetic characteristics as potential covariates (NONMEM(®)). Then, the interaction between darunavir and ritonavir was studied while incorporating levels of both drugs into different inhibitory models. Finally, model-based simulations were performed to compare trough concentrations (Cmin) between the recommended dosage regimen and alternative combinations of darunavir and ritonavir. RESULTS: A one-compartment model with first-order absorption adequately characterized darunavir and ritonavir pharmacokinetics. The between-subject variability in both compounds was important [coefficient of variation (CV%) 34% and 47% for darunavir and ritonavir clearance, respectively]. Lopinavir and ritonavir exposure (AUC) affected darunavir clearance, while body weight and darunavir AUC influenced ritonavir elimination. None of the tested genetic variants showed any influence on darunavir or ritonavir pharmacokinetics. The simulations predicted darunavir Cmin much higher than the IC50 thresholds for wild-type and protease inhibitor-resistant HIV-1 strains (55 and 550 ng/mL, respectively) under standard dosing in >98% of experienced and naive patients. Alternative regimens of darunavir/ritonavir 1200/100 or 1200/200 mg once daily also had predicted adequate Cmin (>550 ng/mL) in 84% and 93% of patients, respectively. Reduction of darunavir/ritonavir dosage to 600/50 mg twice daily led to a 23% reduction in average Cmin, still with only 3.8% of patients having concentrations below the IC50 for resistant strains. CONCLUSIONS: The important variability in darunavir and ritonavir pharmacokinetics is poorly explained by clinical covariates and genetic influences. In experienced patients, treatment simplification strategies guided by drug level measurements and adherence monitoring could be proposed.