Optimizing tuberculosis treatment efficacy: Comparing the standard regimen with Moxifloxacin-containing regimens.

Tuberculosis (TB) continues to be one of the deadliest infectious diseases in the world, causing ~1.5 million deaths every year. The World Health Organization initiated an End TB Strategy that aims to reduce TB-related deaths in 2035 by 95%. Recent research goals have focused on discovering more effective and more patient-friendly antibiotic drug regimens to increase patient compliance and decrease emergence of resistant TB. Moxifloxacin is one promising antibiotic that may improve the current standard regimen by shortening treatment time. Clinical trials and in vivo mouse studies suggest that regimens containing moxifloxacin have better bactericidal activity. However, testing every possible combination regimen with moxifloxacin either in vivo or clinically is not feasible due to experimental and clinical limitations. To identify better regimens more systematically, we simulated pharmacokinetics/pharmacodynamics of various regimens (with and without moxifloxacin) to evaluate efficacies, and then compared our predictions to both clinical trials and nonhuman primate studies performed herein. We used GranSim, our well-established hybrid agent-based model that simulates granuloma formation and antibiotic treatment, for this task. In addition, we established a multiple-objective optimization pipeline using GranSim to discover optimized regimens based on treatment objectives of interest, i.e., minimizing total drug dosage and lowering time needed to sterilize granulomas. Our approach can efficiently test many regimens and successfully identify optimal regimens to inform pre-clinical studies or clinical trials and ultimately accelerate the TB regimen discovery process.

Odor-evoked layer-specific fMRI activities in the awake mouse olfactory bulb.

Awake rodent fMRI is increasingly common over the use of anesthesia since it permits behavioral paradigms and does not confound normal brain function or neurovascular coupling. It is well established that adequate acclimation to the loud fMRI environment and head fixation reduces stress in the rodents and allows for whole brain imaging with little contamination from motion. However, it is unknown whether high-resolution fMRI with increased susceptibility to motion and lower sensitivity can measure small, but spatially discrete, activations in awake mice. To examine this, we used contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI in the mouse olfactory bulb for its enhanced sensitivity and neural specificity. We determined that activation patterns in the glomerular layer to four different odors were spatially distinct and were consistent with previously established histological patterns. In addition, odor-evoked laminar activations were greatest in superficial layers that decreased with laminar depth, similar to previous observations. Interestingly, the fMRI response strengths in the granule cell layer were greater in awake mice than our previous anesthetized rat studies, suggesting that feedback neural activities were intact with wakefulness. We finally determined that fMRI signal changes to repeated odor exposure (i.e., olfactory adaptation) attenuated relatively more in the feedback granule cell layer compared to the input glomerular layer, which is consistent with prior observations. We, therefore, conclude that high-resolution CBVw fMRI can measure odor-specific activation patterns and distinguish changes in laminar activity of head and body restrained awake mice.