Potential role of NF-kappaB in adult neural stem cells: the underrated steersman?

Neural stem cells are precursors of neurons and glial cells. During brain development, these cells proliferate, migrate and differentiate into specific lineages. Recently neural stem cells within the adult central nervous system were identified. Informations are now emerging about regulation of stem cell proliferation, migration and differentiation by numerous soluble factors such as chemokines and cytokines. However, the signal transduction mechanisms downstream of these factors are less clear. Here, we review potential evidences for a novel central role of the transcription factor nuclear factor kappa B (NF-kappaB) in these crucial signal transduction processes. NF-kappaB is an inducible transcription factor detected in neurons, glia and neural stem cells. NF-kappaB was discovered by David Baltimore's laboratory as a transcription factor in lymphocytes. NF-kappaB is involved in many biological processes such as inflammation and innate immunity, development, apoptosis and anti-apoptosis. It has been recently shown that members of the NF-kappaB family are widely expressed by neurons, glia and neural stem cells. In the nervous system, NF-kappaB plays a crucial role in neuronal plasticity, learning, memory consolidation, neuroprotection and neurodegeneration. Recent data suggest an important role of NF-kappaB on proliferation, migration and differentiation of neural stem cells. NF-kappaB is composed of three subunits: two DNA-binding and one inhibitory subunit. Activation of NF-kappaB takes place in the cytoplasm and results in degradation of the inhibitory subunit, thus enabling the nuclear import of the DNA-binding subunits. Within the nucleus, several target genes could be activated. In this review, we suggest a model explaining the multiple action of NF-kappaB on neural stem cells. Furthermore, we discuss the potential role of NF-kappaB within the so-called brain cancer stem cells.

Mathematical model for NF-kappaB-driven proliferation of adult neural stem cells

Neural stem cells (NSCs) are early precursors of neuronal and glial cells. NSCs are capable of generating identical progeny through virtually unlimited numbers of cell divisions (cell proliferation), producing daughter cells committed to differentiation. Nuclear factor kappa B (NF-kappaB) is an inducible, ubiquitous transcription factor also expressed in neurones, glia and neural stem cells. Recently, several pieces of evidence have been provided for a central role of NF-kappaB in NSC proliferation control. Here, we propose a novel mathematical model for NF-kappaB-driven proliferation of NSCs. We have been able to reconstruct the molecular pathway of activation and inactivation of NF-kappaB and its influence on cell proliferation by a system of nonlinear ordinary differential equations. Then we use a combination of analytical and numerical techniques to study the model dynamics. The results obtained are illustrated by computer simulations and are, in general, in accordance with biological findings reported by several independent laboratories. The model is able to both explain and predict experimental data. Understanding of proliferation mechanisms in NSCs may provide a novel outlook in both potential use in therapeutic approaches, and basic research as well.

Highly efficient neural differentiation of human somatic stem cells, isolated by minimally invasive periodontal surgery

Neural stem cells (NSCs) are potential sources for cell therapy of neurodegenerative diseases and for drug screening. Despite their potential benefits, ethical and practical considerations limit the application of NSCs derived from human embryonic stem cells (ES) or adult brain tissue. Thus, alternative sources are required to satisfy the criteria of ready accessibility, rapid expansion in chemically defined media and reliable induction to a neuronal fate. We isolated somatic stem cells from the human periodontium that were collected during minimally invasive periodontal access flap surgery as part of guided tissue regeneration therapy. These cells could be propagated as neurospheres in serum-free medium, which underscores their cranial neural crest cell origin. Culture in the presence of epidermal growth factor (EGF) and fibroblast growth factor-2 (FGF-2) under serum-free conditions resulted in large numbers of nestin-positive/Sox-2-positive NSCs. These periodontium-derived (pd) NSCs are highly proliferative and migrate in response to chemokines that have been described as inducing NSC migration. We used immunocytochemical techniques and RT-PCR analysis to assess neural differentiation after treatment of the expanded cells with a novel induction medium. Adherence to substrate, growth factor deprivation, and retinoic acid treatment led to the acquisition of neuronal morphology and stable expression of markers of neuronal differentiation by more than 90% of the cells. Thus, our novel method might provide nearly limitless numbers of neuronal precursors from a readily accessible autologous adult human source, which could be used as a platform for further experimental studies and has potential therapeutic implications.

Radiative forcing and climate metrics for ozone precursor emissions: the impact of multi-model averaging

Multi-model ensembles are frequently used to assess understanding of the response of ozone and methane lifetime to changes in emissions of ozone precursors such as NOx, VOCs (volatile organic compounds) and CO. When these ozone changes are used to calculate radiative forcing (RF) (and climate metrics such as the global warming potential (GWP) and global temperature-change potential (GTP)) there is a methodological choice, determined partly by the available computing resources, as to whether the mean ozone (and methane) concentration changes are input to the radiation code, or whether each model's ozone and methane changes are used as input, with the average RF computed from the individual model RFs. We use data from the Task Force on Hemispheric Transport of Air Pollution source–receptor global chemical transport model ensemble to assess the impact of this choice for emission changes in four regions (East Asia, Europe, North America and South Asia). We conclude that using the multi-model mean ozone and methane responses is accurate for calculating the mean RF, with differences up to 0.6% for CO, 0.7% for VOCs and 2% for NOx. Differences of up to 60% for NOx 7% for VOCs and 3% for CO are introduced into the 20 year GWP. The differences for the 20 year GTP are smaller than for the GWP for NOx, and similar for the other species. However, estimates of the standard deviation calculated from the ensemble-mean input fields (where the standard deviation at each point on the model grid is added to or subtracted from the mean field) are almost always substantially larger in RF, GWP and GTP metrics than the true standard deviation, and can be larger than the model range for short-lived ozone RF, and for the 20 and 100 year GWP and 100 year GTP. The order of averaging has most impact on the metrics for NOx, as the net values for these quantities is the residual of the sum of terms of opposing signs. For example, the standard deviation for the 20 year GWP is 2–3 times larger using the ensemble-mean fields than using the individual models to calculate the RF. The source of this effect is largely due to the construction of the input ozone fields, which overestimate the true ensemble spread. Hence, while the average of multi-model fields are normally appropriate for calculating mean RF, GWP and GTP, they are not a reliable method for calculating the uncertainty in these fields, and in general overestimate the uncertainty.