हमारा समूह 1000 से अधिक वैज्ञानिक सोसायटी के सहयोग से हर साल संयुक्त राज्य अमेरिका, यूरोप और एशिया में 3000+ वैश्विक सम्मेलन श्रृंखला कार्यक्रम आयोजित करता है और 700+ ओपन एक्सेस जर्नल प्रकाशित करता है जिसमें 50000 से अधिक प्रतिष्ठित व्यक्तित्व, प्रतिष्ठित वैज्ञानिक संपादकीय बोर्ड के सदस्यों के रूप में शामिल होते हैं।
ओपन एक्सेस जर्नल्स को अधिक पाठक और उद्धरण मिल रहे हैं
700 जर्नल और 15,000,000 पाठक प्रत्येक जर्नल को 25,000+ पाठक मिल रहे हैं
Axel Dalhoff *,Sabine Schubert
Objectives: Protein binding decreases antibacterial activities as the free fraction only crosses membranes thus reaching intracellular targets. However, serum components may increase antibacterial activities. Therefore, the effect of serum proteins on activities of ß-lactams and macrolides was examined.
Methods: Strains with defined resistance genotypes were selected; MRSA, ermB-, mefA-, gyrA Ser81-Phemutants of S. pneumoniae, and TEM-1 or TEM-3 ß-lactamase producing E. coli were used. Ten antibiotics known to penetrate into bacteria either well or poorly and/or known to be labile or stable to inactivation by ß-lactamases were used. Strains were incubated in Brain Heart Infusion Broth (BHI), BHI +50% heat inactivated human serum or active serum, or 45 g/L albumin. MICs were determined and Kill-kinetics was recorded following exposure to constant or fluctuating drug concentrations. Kill constants and areas under the bacterial kill curves were calculated.
Results: Albumin and inactive serum increased MICs and reduced kill rates of the agents studied in conformity with their protein binding. However, active serum increased the activities of such agents known to penetrate poorly into strains with permeation barriers. In addition, active as well as inactive serum restored the activities of ß-lactams against ß-lactamase producing strains due to enzyme inhibition.
Conclusions: Serum proteins permeabilized bacteria and inhibited ß-lactamase activity. The impact of serum proteins on antibacterial activities against specific drug-bug associations is more than predicted by considering the numerical value of protein binding alone.