Maciel, E. | Search bioRxiv

bioRxiv2021

Restoration of DNA Integrity and Cell Cycle by Electric Stimulation in Planarian Tissues Damaged by Ionizing Radiation

Exposure to high levels of ionizing {gamma}-radiation leads to irreversible DNA damage and cell death. Here, we establish that exogenous application of electric stimulation enables cellular plasticity to reestablish stem cell activity in tissues damaged by ionizing radiation. We show that sub-threshold direct current stimulation (DCS) rapidly restores pluripotent stem cell populations previously eliminated by lethally {gamma}-irradiated tissues of the planarian flatworm Schmidtea mediterranea. Our findings reveal that DCS enhances DNA repair, transcriptional activity, and cell cycle entry in post-mitotic cells. These responses involve rapid increases in cytosolic [Ca2+] through the activation of L-type Cav channels and intracellular Ca2+ stores leading to the activation of immediate early genes and ectopic expression of stem cell markers in postmitotic cells. Overall, we show the potential of electric current stimulation to reverse damaging effects of high dose {gamma}-radiation in adult tissues. Furthermore, our results provide mechanistic insights describing how electric stimulation effectively translates into molecular responses capable of regulating fundamental cellular functions without the need for genetic or pharmacological intervention.

developmental biology↗

bioRxiv2018

Introducing risk inequality metrics in tuberculosis policy development

Global stakeholders including the World Health Organization rely on predictive models for developing strategies and setting targets for tuberculosis care and control programs. Failure to account for variation in individual risk leads to substantial biases that impair data interpretation and policy decisions1,2. Anticipated impediments to estimating heterogeneity for each parameter are discouraging despite considerable technical progress in recent years. Here we identify acquisition of infection as the single process where heterogeneity most fundamentally impacts model outputs, due to cohort selection imposed by dynamic forces of infection. Individuals with higher risk of acquiring infection are predominantly affected by the pathogen, leaving the unaffected pool with those whose intrinsic risk is lower. This causes susceptibility pools to attain average risks which are lower under higher forces of infection. Interventions that modify the force of infection change the strength of selection, and therefore alter average risks in the pools which feed further incidence. Inability to account for these dynamics is what makes homogenous models unsuitable. We introduce concrete metrics to approximate risk inequality in tuberculosis, demonstrate their utility in mathematical models, and pack the information into a risk inequality coefficient which can be calculated and reported by national tuberculosis programs for use in policy development and modeling.

epidemiology↗