Effect of rifampicin and doxycycline on the chemiluminescence of leukocytes]

The effect of rifampicin and doxycycline on spontaneous and zymosan-induced chemiluminescence of polymorphonuclear leukocytes was studied on guinea pigs. The cells were incubated in the presence of the antibiotics, washed and stimulated by zymosan. Under such conditions rifampicin in therapeutic doses of 0.1 to 10 micrograms/kg and doxycycline in a dose of 100 micrograms/kg potentiated the leukocyte chemiluminescence. Investigation of the antibiotics effect on the cells without washing failed because of the direct interference of rifampicin and doxycycline with the cell-independent stage of the chemiluminescent reaction.     

Effect of rifampicin on tryptophanase induction in normal and rifampicin-resistantVibrio el tor

The induction of tryptophanase was not affected by rifampicin in the rifampicin-resistant mutant ofVibrio el tor while the antibiotic inhibited the induction of tryptophanase in the normal strain at level of ribonucleic acid and protein synthesis.     

Effect of rifampicin on development of tolerance to analgesic actions.

Two series of experiments were performed. In the first series the reaction times of mice were determined using the hotplate technique. In the second series of experiments the reactions of rats were determined using the electric footshock technique. In both series of experiments morphine was observed to alter the responses, and chronic morphine administration resulted in tolerance to these actions of morphine. In both series of experiments, tolerance, defined by these same criteria, was inhibited by the concurrent administration of rifampicin.     

Compatibility of R-factors in naturally occurring enteric bacteria]

The compatibility of four wild type fi+R factors to R1 factor, a representative of the FII compatibility group of F-like class of the plasmids was studied. Two of them (R448 and R459) were incompatible to the R1 factor at selective for R448 and R459 donors conditions. The recipient R1 factor elimination apparently takes place at the first generations of conjugants. The compatibility of these R plasmids to R1 is possible at selective for donor and recipient plasmids conditions. R459 and R1 factors were transfered to Escherichia coli W945 simultaneously and recombination between them was suggested. B211 and R215 factors are compatible to R1 factor and their coexistence with the last is stable despite whether conjugants were selected on one or two R plasmids principle. Further conjugants transfer R211 and R215 only, but not R1. It is concluded that R factors No 448 and No 459 are of FII group compatibility. R211 and R215 factors group compatibility is still unknown.     

Effect of rifampicin on the infectivity of RNA bacteriophage f2.

RNA bacteriophage f2, treated in vitro with rifampicin, loses infectivity dramatically. Rifampicin interacts with phage RNA, binding to a few specific sites. Inhibition of phage RNA infectivity occurs at 10-100 times lower molar excess of rifampicin than inhibition of infectivity of intact phage particles. Thus the phage capsid acts as a barrier, diminishing interaction of the drug with phage RNA.     

Testing the stability of transfer functions

In dendroclimatology, testing the stability of transfer functions using cross-calibration verification (CCV) statistics is a common procedure. However, the frequently used statistics reduction of error (RE) and coefficient of efficiency (CE) merely assess the skill of reconstruction for the validation period, which does not necessarily reflect possibly instable regression parameters. Furthermore, the frequently used rigorous threshold of zero which sharply distinguishes between valid and invalid transfer functions is prone to an underestimation of instability. To overcome these drawbacks, we here introduce a new approach – the Bootstrapped Transfer Function Stability test (BTFS). BTFS relies on bootstrapped estimates of the change of model parameters (intercept, slope, and r²) between calibration and verification period as well as the bootstrapped significance of corresponding models. A comparison of BTFS, CCV and a bootstrapped CCV approach (BCCV) applied to 42,000 pseudo-proxy datasets with known properties revealed that BTFS responded more sensitively to instability compared to CCV and BCCV. BTFS performance was significantly affected by sample size (length of calibration period) and noise (explained variance between predictor and predictand). Nevertheless, BTFS performed superior with respect to the detection of instable transfer functions in comparison to CCV.