Co-condensation between transcription factor and coactivator p300 modulates transcriptional bursting kinetics.

The coactivator p300/CREB-binding protein (CBP) regulates genes by facilitating the assembly of transcriptional machinery and by acetylating histones and other factors. However, it remains mostly unclear how both functions of p300 are dynamically coordinated during gene control. Here, we showed that p300 can orchestrate two functions through the formation of dynamic clusters with certain transcription factors (TFs), which is mediated by the interactions between a TF's transactivation domain (TAD) and the intrinsically disordered regions of p300. Co-condensation can enable spatially defined, all-or-none activation of p300's catalytic activity, priming the recruitment of coactivators, including Brd4. We showed that co-condensation can modulate transcriptional initiation rate and burst duration of target genes, underlying nonlinear gene regulatory functions. Such modulation is consistent with how p300 might shape gene bursting kinetics globally. Altogether, these results suggest an intriguing gene regulation mechanism, in which TF and p300 co-condensation contributes to transcriptional bursting regulation and cooperative gene control.

Derivation of no significant risk levels for three lower acrylates: Conclusions and recommendations from an expert panel.

A panel of toxicology, mode of action (MOA), and cancer risk assessment experts was engaged to derive no-significant-risk-levels (NSRLs) for three lower acrylates: methyl acrylate (MA), ethyl acrylate (EA), and 2-ethylhexyl acrylate (2EHA) using the best available science, data, and methods. The review was structured as a five-round, modified Delphi format, a systematic process for collecting independent and deliberative input from panel members, and it included several procedural elements to reduce potential sources of bias and groupthink. Input from the panel for key decisions in the dose-response assessments resulted in NSRL values of 530 µg/day (330-800 µg/day), 640 µg/day (280-670 µg/day), and 1700 µg/day (1300-2700 µg/day) for MA, EA, and 2EHA, respectively. Novel to this approach were the use of nonneoplastic lesions reported at point of contact where tumors have been reported in laboratory rodents, along with nonlinear extrapolation to low doses (uncertainty factor approach) based upon panel recommendations. Confidence in these values is considered medium to high for exposures applied to the routes of exposure tested (inhalation for MA and EA, dermal for 2EHA), but confidence is considered lower when applied to other routes of exposure.

Implications of nonlinearity, confounding, and interactions for estimating exposure concentration-response functions in quantitative risk analysis.

Recent advances in understanding of biological mechanisms and adverse outcome pathways for many exposure-related diseases show that certain common mechanisms involve thresholds and nonlinearities in biological exposure concentration-response (C-R) functions. These range from ultrasensitive molecular switches in signaling pathways, to assembly and activation of inflammasomes, to rupture of lysosomes and pyroptosis of cells. Realistic dose-response modeling and risk analysis must confront the reality of nonlinear C-R functions. This paper reviews several challenges for traditional statistical regression modeling of C-R functions with thresholds and nonlinearities, together with methods for overcoming them. Statistically significantly positive exposure-response regression coefficients can arise from many non-causal sources such as model specification errors, incompletely controlled confounding, exposure estimation errors, attribution of interactions to factors, associations among explanatory variables, or coincident historical trends. If so, the unadjusted regression coefficients do not necessarily predict how or whether reducing exposure would reduce risk. We discuss statistical options for controlling for such threats, and advocate causal Bayesian networks and dynamic simulation models as potentially valuable complements to nonparametric regression modeling for assessing causally interpretable nonlinear C-R functions and understanding how time patterns of exposures affect risk. We conclude that these approaches are promising for extending the great advances made in statistical C-R modeling methods in recent decades to clarify how to design regulations that are more causally effective in protecting human health.

Radio-biologically motivated modeling of radiation risks of mortality from ischemic heart diseases in the Canadian fluoroscopy cohort study.

Recent analyses of the Canadian fluoroscopy cohort study reported significantly increased radiation risks of mortality from ischemic heart diseases (IHD) with a linear dose-response adjusted for dose fractionation. This cohort includes 63,707 tuberculosis patients from Canada who were exposed to low-to-moderate dose fractionated X-rays in 1930s-1950s and were followed-up for death from non-cancer causes during 1950-1987. In the current analysis, we scrutinized the assumption of linearity by analyzing a series of radio-biologically motivated nonlinear dose-response models to get a better understanding of the impact of radiation damage on IHD. The models were weighted according to their quality of fit and were then mathematically superposed applying the multi-model inference (MMI) technique. Our results indicated an essentially linear dose-response relationship for IHD mortality at low and medium doses and a supra-linear relationship at higher doses (> 1.5 Gy). At 5 Gy, the estimated radiation risks were fivefold higher compared to the linear no-threshold (LNT) model. This is the largest study of patients exposed to fractionated low-to-moderate doses of radiation. Our analyses confirm previously reported significantly increased radiation risks of IHD from doses similar to those from diagnostic radiation procedures.

Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003.

The scientific community faces important discussions on the validity of the linear no-threshold (LNT) model for radiation-associated cardiovascular diseases at low and moderate doses. In the present study, mortalities from cerebrovascular diseases (CeVD) and heart diseases from the latest data on atomic bomb survivors were analyzed. The analysis was performed with several radio-biologically motivated linear and nonlinear dose-response models. For each detrimental health outcome one set of models was identified that all fitted the data about equally well. This set was used for multi-model inference (MMI), a statistical method of superposing different models to allow risk estimates to be based on several plausible dose-response models rather than just relying on a single model of choice. MMI provides a more accurate determination of the dose response and a more comprehensive characterization of uncertainties. It was found that for CeVD, the dose-response curve from MMI is located below the linear no-threshold model at low and medium doses (0-1.4 Gy). At higher doses MMI predicts a higher risk compared to the LNT model. A sublinear dose-response was also found for heart diseases (0-3 Gy). The analyses provide no conclusive answer to the question whether there is a radiation risk below 0.75 Gy for CeVD and 2.6 Gy for heart diseases. MMI suggests that the dose-response curves for CeVD and heart diseases in the Lifespan Study are sublinear at low and moderate doses. This has relevance for radiotherapy treatment planning and for international radiation protection practices in general.

A model of cytotoxic dose-response nonlinearities arising from adaptive cell inventory management in tissues.

Why do low-level exposures to environmental toxins often elicit over-compensating responses that reduce risk to an organism? Conversely, if these responses improve health, why wait for an environmental challenge to trigger them? This paper presents a mathematical modeling framework that addresses both questions using the principle that evolution favors tissues that hedge their bets against uncertain environmental challenges. We consider a tissue composed of differentiated cells performing essential functions (e.g., lung tissue, bone marrow, etc.). The tissue seeks to maintain adequate supplies of these cells, but many of them may occasionally be killed relatively quickly by cytotoxic challenges. The tissue can "order replacements" (e.g., via cytokine network signaling) from a deeper compartment of proliferative stem cells, but there is a delivery lag because these cells must undergo maturation, amplification via successive divisions, and terminal differentiation before they can replace the killed functional cells. Therefore, a "rational" tissue maintains an inventory of relatively mature cells (e.g., the bone marrow reserve for blood cells) for quick release when needed. This reservoir is replenished by stimulating proliferation in the stem cell compartment. Normally, stem cells have a very low risk of unrepaired carcinogenic (or other) damage, due to extensive checking and repair. But when production is rushed to meet extreme demands, error rates increase. We use a mathematical model of cell inventory management to show that decision rules that effectively manage the inventory of mature cells to maintain tissue function across a wide range of unpredictable cytotoxic challenges imply that increases in average levels of cytotoxic challenges can increase average inventory levels and reduce the average error rate in stem cell production. Thus, hormesis and related nonlinearities can emerge as a natural result of cell-inventory risk management by tissues.

Low doses of gamma-radiation induce nonlinear dose responses in Mammalian and plant cells.

The percentage of cells with chromosome aberrations or micronuclei induced by low doses of acute (dose rate of 47 cGy/min) or chronic (dose rate of 0.01 cGy/min) gamma-irradiation was studied in vitro in Chinese hamster fibroblasts, human lymphocytes, and Vicia faba seeds and seedlings. The sensitivity of the indicated biological entities to low doses was greater than expected based on linear extrapolation from higher doses. The dose-response curves for cytogenetic damage that were obtained were nonlinear when evaluated over the full range of the doses used. At very low doses, the dose-response curves appeared linear, followed by a plateau region at intermediate doses. At high doses the dose response curves again appeared linear with a slope different from that for the low-dose region. There was no statistically significant difference between the yields of cells with micronuclei induced by low doses of acute versus chronic irradiation. Similar data were obtained both for human lymphocyte culture and for roots and seeds of Vicia faba. Our experiments revealed that the dose range over which the plateau occurs depends on the type of cells irradiated. We have also shown that the modifying effects of the repair inhibitor caffeine and the radioprotector mercaptoethylenamine (MEA) are absent at low doses of gamma irradiation and that caffeine increased the number of cells with cytogenetic damage when evaluated over the plateau region. In the presence of MEA, the upper end of the plateau region was extended from just above 1 Gy to about 2 Gy. We therefore provide direct evidence that a plateau exists in the dose-response curve for the indicated radiation-induced stochastic effects. Furthermore, our results suggest that, for low linear energy transfer radiation, the induction of DNA repair occurs only after a threshold level of cytogenetic damage and that the higher yield of cytogenetic damage per unit dose at low radiation doses is attributable to an insignificant contribution or the absence of DNA repair processes.

Radiation-induced change in lymphocyte proliferation and its neuroendocrine regulation: dose-response relationship and pathophysiological implications.

Cellular activities are regulated by intracellular signals initiated by stimulation from the external and internal environments. Different signal pathways are involved in the initiation of different cellular functions. In connection with cell proliferation in response to mitogenic stimulation, the dose-effect relationship of the magnitude of (3)H-TdR incorporation into lymphocytes after exposure to different concentrations of concanavalin A (Con A) showed an inverted U-shaped curve in the concentration range 2-30 mug/ml. In previous studies it has been observed that the stimulatory effect of Con A (5 mug/ml) on lymphocyte proliferation was potentiated by whole-body irradiation (WBI) with low dose (0.075 Gy) and suppressed by WBI with high dose (2 Gy). When different concentrations of corticosterone, ranging from 10(-12) to 10(-7) M, were added to the Con A-stimulated lymphocytes, low-concentration stimulation and high-concentration suppression of lymphocyte proliferation were demonstrated. In the presence of 5 x10 (-12) M (subphysiological concentration) of corticosterone the proliferation of thymocytes and splenic T cells in response to Con A was further up-regulated after low-dose radiation. Low-dose radiation (0.075 Gy) caused lowering of serum ACTH and corticosterone concentration as well as down-regulated transcription of the hypothalamic proopiomelanocortin gene. The present paper intends to show that multiple neurohormonal factors, including the pineal gland and neurotransmitters, in addition to the hypothalamic-pituitary-adrenocortical axis, are involved in the stimulation of immune responses induced by low-dose ionizing radiation. The complex nature of the interrelationship between the intracellular signaling of lymphocytes and the neuroendocrine regulation after WBI is discussed.