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This paper reevaluates the first report of X-ray-induced somatic gene mutations. It was undertaken by John Patterson, Department Chair of Hermann Muller, using the same biological model, methods and equipment of Muller. Patterson reported X-ray induced mutation frequencies for X-chromosome-linked (sex-linked) recessive gene mutations in somatic cells of Drosophila melanogaster that resulted in color changes in the ommatidia of the eyes. Results were based on color changes detected in both male and female offspring irradiated while in egg, larval or pupal stages and for unirradiated controls. Patterson claimed that the observed dose response displayed linearity, with a clear implication that the linear response extended to background exposure levels of unirradiated controls. This reanalysis disputes Patterson's interpretation, showing that the dose response in the low-dose zone strongly supported a threshold model. The doses in the experiment, which were not clearly presented, were so high that it would preclude the assumption that the experiment provided any information of relevance to radiation exposures of humans at low doses, or even at high doses delivered at low-dose rates. Induced phenotypical changes that occurred at the higher doses, especially in female offspring, overwhelmingly resulted from X-ray-induced chromosome breaks instead of point mutations as initially expected by Patterson. The Patterson findings and linearity interpretations were an important contributory factor in the acceptance of the linear non-threshold (LNT) model during the formative time of concept consolidation. It is rather shocking now to see that the actual data provided no support for the LNT model.

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PURPOSE: α-Klotho has been linked to insulin resistance (IR) in basic research. However, experimental evidence is inconsistent, and there is a lack of data from human research. This study seeks to elucidate the association of α-Klotho with IR in a nationwide, multiracial population. METHODS: A total of 5289 participants aged 40-79 years were included in the National Health and Nutrition Examination Survey (NHANES) spanning 2007-2016. Serum α-Klotho was measured using enzyme-linked immunosorbent assays (ELISA), and IR was evaluated by the homeostatic model assessment of insulin resistance (HOMA-IR). Weighted multivariate logistic and linear regression analysis, subgroup analysis stratified by demographic characteristics, medical condition or obesity status, and sensitivity analysis using propensity score matching (PSM) were performed. Restricted cubic splines (RCS) were performed to explore the nonlinear relationship. RESULTS: In the fully adjusted logistic regression model, a significant positive association was observed between log-transformed α-Klotho and IR (OR = 3.63, 95% CI: 1.56, 8.45), particularly in males or nonobese individuals (Pinteraction < 0.05). In the linear regression model, log10(α-Klotho) was associated with fasting blood glucose (FBG, ß = 1.25, 95% CI: 0.74, 1.76) and glycosylated hemoglobin (HbA1c, ß = 0.49, 95% CI: 0.20, 0.77). RCS revealed an inverse L-shaped dose-response relationship of α-Klotho with FBG and HbA1c (Pnonlinear <0.05). Beyond the inflection point of log10(α-Klotho) at 2.79, ß coefficients sharply rose for these glycaemic control indicators. CONCLUSION: The study provides clinical evidence supporting a positive association between α-Klotho and IR. Moreover, the inverse L-shaped relationship suggests that α-Klotho should reach a certain level to predict glycaemic changes effectively.

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In his Nobel Prize Lecture of December 12, 1946, Hermann J. Muller argued that the dose-response for ionizing radiation-induced germ cell mutations was linear and that there was ''no escape from the conclusion that there is no threshold''. However, a newly discovered commentary by the Robert L. Brent (2015) indicated that Curt Stern, after reading a draft of part of Muller's Nobel Prize Lecture, called Muller, strongly advising him to remove reference to the flawed linear non-threshold (LNT)-supportive Ray-Chaudhuri findings and strongly encouraged him to be guided by the threshold supportive data of Ernst Caspari. Brent indicated that Stern recounted this experience during a genetics class at the University of Rochester. Brent wrote that Muller refused to follow Stern's advice, thereby proclaiming support for the LNT dose-response while withholding evidence that was contrary during his Nobel Prize Lecture. This finding is of historical importance since Muller's Nobel Prize Lecture gained considerable international attention and was a turning point in the acceptance of the linearity model for radiation and chemical hereditary and carcinogen risk assessment.

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This paper assesses the judgments of leading radiation geneticists and cancer risk assessment scientists from the mid-1950s to mid-1970s that background radiation has a significant effect on human genetic disease and cancer incidence. This assumption was adopted by the National Academy of Sciences (NAS) Biological Effects of Atomic Radiation (BEAR) I Genetics Panel for genetic diseases and subsequently applied to cancer risk assessment by other leading individuals/advisory groups (e.g., International Commission on Radiation Protection-ICRP). These recommendations assumed that a sizeable proportion of human mutations originated from background radiation due to cumulative exposure over prolonged reproductive periods and the linear nature of the dose-response. This paper shows that the assumption that background radiation is a significant cause of spontaneous mutation, genetic diseases, and cancer incidence is not supported by experimental and epidemiological findings, and discredits erroneous risk assessments that improperly influenced the recommendations of national and international advisory committees, risk assessment policies, and beliefs worldwide.

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This opinion of the Senate Commission on Food Safety (SKLM) of the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) presents arguments for an updated risk assessment of diet-related exposure to acrylamide (AA), based on a critical review of scientific evidence relevant to low dose exposure. The SKLM arrives at the conclusion that as long as an appropriate exposure limit for AA is not exceeded, genotoxic effects resulting in carcinogenicity are unlikely to occur. Based on the totality of the evidence, the SKLM considers it scientifically justified to derive a tolerable daily intake (TDI) as a health-based guidance value.

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The present paper reports the discovery of an October 26, 1927 letter of Hermann J. Muller concerning the owner and editor of the journal Science that suggests an agreement that could have led to Muller's publication in Science - absent any data - which was contributory to both his professional reputation, and perhaps his being considered for and awarded a Nobel Prize.

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This paper demonstrates that the dissertation research of Ray-Chaudhuri (1939, 1944) that was used by Hermann Muller to support his radiation induced gene mutation hypothesis and linear non-threshold (LNT) dose response model during his Nobel Prize Lecture is "uninterpretable" with respect to these issues. The research failed to include essential research design information, resulting in reporting flaws that have never been previously identified. These observations are historically important because this dissertation was used to blunt powerful criticism of Muller's gene mutation research and strongly promoted his advocacy of the LNT model in radiation risk assessment.

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BACKGROUND: The genotoxic and cancerogenic impacts of population-wide cannabinoid exposure remains an open but highly salient question. The present report examines these issues from a continuous bivariate perspective with subsequent reports continuing categorical and detailed analyses. METHODS: Age-standardized state census incidence of 28 cancer types (including "All (non-skin) Cancer") was sourced using SEER*Stat software from Centres for Disease Control and National Cancer Institute across US states 2001-2017. It was joined with drug exposure data from the nationally representative National Survey of Drug Use and Health conducted annually by the Substance Abuse and Mental Health Services Administration 2003-2017, response rate 74.1%. Cannabinoid data was from Federal seizure data. Income and ethnicity data sourced from the US Census Bureau. Data was processed in R. RESULTS: Nineteen thousand eight hundred seventy-seven age-standardized cancer rates were returned. Based on these rates and state populations this equated to 51,623,922 cancer cases over an aggregated population 2003-2017 of 124,896,418,350. Regression lines were charted for cancer-substance exposures for cigarettes, alcohol use disorder (AUD), cannabis, THC, cannabidiol, cannabichromene, cannabinol and cannabigerol. In this substance series positive trends were found for 14, 9, 6, 9, 12, 6, 9 and 7 cancers; with largest minimum E-Values (mEV) of 1.76 × 109, 4.67 × 108, 2.74 × 104, 4.72, 2.34 × 1018, 2.74 × 1017, 1.90 × 107, 5.05 × 109; and total sum of exponents of mEV of 34, 32, 13, 0, 103, 58, 25, 31 indicating that cannabidiol followed by cannabichromene are the most strongly implicated in environmental carcinogenesis. Breast cancer was associated with tobacco and all cannabinoids (from mEV = 3.53 × 109); "All Cancer" (non-skin) linked with cannabidiol (mEV = 1.43 × 1011); pediatric AML linked with cannabis (mEV = 19.61); testicular cancer linked with THC (mEV = 1.33). Cancers demonstrating elevated mEV in association with THC were: thyroid, liver, pancreas, AML, breast, oropharynx, CML, testis and kidney. Cancers demonstrating elevated mEV in relation to cannabidiol: prostate, bladder, ovary, all cancers, colorectum, Hodgkins, brain, Non-Hodgkins lymphoma, esophagus, breast and stomach. CONCLUSION: Data suggest that cannabinoids including THC and cannabidiol are important community carcinogens exceeding the effects of tobacco or alcohol. Testicular, (prostatic) and ovarian tumours indicate mutagenic corruption of the germline in both sexes; pediatric tumourigenesis confirms transgenerational oncogenesis; quantitative criteria implying causality are fulfilled.

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BACKGROUND: As the cannabis-cancer relationship remains an important open question epidemiological investigation is warranted to calculate key metrics including Rate Ratios (RR), Attributable Fractions in the Exposed (AFE) and Population Attributable Risks (PAR) to directly compare the implicated case burden between emerging cannabinoids and the established carcinogen tobacco. METHODS: SEER*Stat software from Centres for Disease Control was used to access age-standardized state census incidence of 28 cancer types (including "All (non-skin) Cancer") from National Cancer Institute in US states 2001-2017. Drug exposures taken from the National Survey of Drug Use and Health 2003-2017, response rate 74.1%. Federal seizure data provided cannabinoid exposure. US Census Bureau furnished income and ethnicity. Exposure dichotomized as highest v. lowest exposure quintiles. Data processed in R. RESULTS: Nineteen thousand eight hundred seventy-seven age-standardized cancer rates were returned. Based on these rates and state populations this equated to 51,623,922 cancer cases over an aggregated population 2003-2017 of 124,896,418,350. Fifteen cancers displayed elevated E-Values in the highest compared to the lowest quintiles of cannabidiol exposure, namely (in order): prostate, melanoma, Kaposi sarcoma, ovarian, bladder, colorectal, stomach, Hodgkins, esophagus, Non-Hodgkins lymphoma, All cancer, brain, lung, CLL and breast. Eleven cancers were elevated in the highest THC exposure quintile: melanoma, thyroid, liver, AML, ALL, pancreas, myeloma, CML, breast, oropharynx and stomach. Twelve cancers were elevated in the highest tobacco quintile confirming extant knowledge and study methodology. For cannabidiol RR declined from 1.397 (95%C.I. 1.392, 1.402), AFE declined from 28.40% (28.14, 28.66%), PAR declined from 15.3% (15.1, 15.5%) and minimum E-Values declined from 2.13. For THC RR declined from 2.166 (95%C.I. 2.153, 2.180), AFE declined from 53.8% (53.5, 54.1%); PAR declined from 36.1% (35.9, 36.4%) and minimum E-Values declined from 3.72. For tobacco, THC and cannabidiol based on AFE this implies an excess of 93,860, 91,677 and 48,510 cases; based on PAR data imply an excess of 36,450, 55,780 and 14,819 cases. CONCLUSION: Data implicate 23/28 cancers as being linked with THC or cannabidiol exposure with epidemiologically-causal relationships comparable to those for tobacco. AFE-attributable cases for cannabinoids (91,677 and 48,510) compare with PAR-attributable cases for tobacco (36,450). Cannabinoids constitute an important multivalent community carcinogen.

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BACKGROUND: The epidemiology of cannabinoid-related cancerogenesis has not been studied with cutting edge epidemiological techniques. Building on earlier bivariate papers in this series we aimed to conduct pathfinding studies to address this gap in two tumours of the reproductive tract, prostate and ovarian cancer. METHODS: Age-standardized cancer incidence data for 28 tumour types (including "All (non-skin) Cancer") was sourced from Centres for Disease Control and National Cancer Institute using SEER*Stat software across US states 2001-2017. Drug exposure was sourced from the nationally representative household survey National Survey of Drug Use and Health conducted annually by the Substance Abuse and Mental Health Services Administration 2003-2017 with response rate 74.1%. Federal seizure data provided cannabinoid concentration data. US Census Bureau provided income and ethnicity data. Inverse probability weighted mixed effects, robust and panel regression together with geospatiotemporal regression analyses were conducted in R. E-Values were also calculated. RESULTS: 19,877 age-standardized cancer rates were returned. Based on these rates and state populations this equated to 51,623,922 cancer cases over an aggregated population 2003-2017 of 124,896,418,350. Inverse probability weighted regressions for prostate and ovarian cancers confirmed causal associations robust to adjustment. Cannabidiol alone was significantly associated with prostate cancer (ß-estimate = 1.61, (95%C.I. 0.99, 2.23), P = 3.75 × 10- 7). In a fully adjusted geospatiotemporal model at one spatial and two temporal years lags cannabidiol was significantly independently associated with prostate cancer (ß-estimate = 2.08, (1.19, 2.98), P = 5.20 × 10- 6). Cannabidiol alone was positively associated with ovarian cancer incidence in a geospatiotemporal model (ß-estimate = 0.36, (0.30, 0.42), P <  2.20 × 10- 16). The cigarette: THC: cannabidiol interaction was significant in a fully adjusted geospatiotemporal model at six years of temporal lag (ß-estimate = 1.93, (1.07, 2.78), P = 9.96 × 10- 6). Minimal modelled polynomial E-Values for prostate and ovarian cancer ranged up to 5.59 × 1059 and 1.92 × 10125. Geotemporospatial modelling of these tumours showed that the cannabidiol-carcinogenesis relationship was supra-linear and highly sigmoidal (P = 1.25 × 10- 45 and 12.82 × 10- 52 for linear v. polynomial models). CONCLUSION: Cannabinoids including THC and cannabidiol are therefore important community carcinogens additive to the effects of tobacco and greatly exceeding those of alcohol. Reproductive tract carcinogenesis necessarily implies genotoxicity and epigenotoxicity of the germ line with transgenerational potential. Pseudoexponential and causal dose-response power functions are demonstrated.

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This paper evaluates the scientific basis for the adoption of the linear non-threshold (LNT) dose response model for radiation-induced leukemia. This LNT risk assessment application for leukemia is significant because it: (1) was generalized for all tumor types induced by ionizing radiation and chemical carcinogens at relatively high doses and; (2) it was based on the mechanistic assumption of low dose linearity for somatic cell mutations as determined from responses in mature spermatozoa of fruit flies. A serious problem with the latter assumption is that those spermatozoa lack DNA repair. The acceptance of the LNT dose response model for cancer risk assessment was based on the convergence of recommendations of the BEAR I Genetics Panel (1956a) for reproductive cell gene mutations and those of Lewis (1957a) for somatic cell mutation and its capacity to explain apparent and/or predicted linear dose responses of ionizing radiation-induced leukemia in multiple and diverse epidemiological investigations. Use of that model and related dose response beliefs achieved rapid, widespread and enduring acceptance in the scientific and regulatory communities. They provide the key historical foundation for the sustained LNT-based policy for cancer risk assessment to the present. While previous papers in this series have challenged key scientific assessments and ethical foundations of the BEAR I Genetics Panel, the present paper provides evidence that Lewis: 1) incorrectly interpreted the fundamental scientific studies used to support the LNT conclusion even though such studies show consistent hormetic-J-shaped dose response relationships for leukemia in Hiroshima and Nagasaki survivors; and, 2) demonstrated widespread bias in support of an LNT conclusion and related policies, which kept him from making an objective and fair assessment. The LNT recommendation appears to have been uncritically accepted and integrated into scientific and regulatory practice in large part because it inappropriately appealed to existing authority and it garnered the support of those who were willing to risk greatly exaggerating the public's fears of environmentally-induced disease, such as enhanced risk of leukemia, with the goal of stopping the atmospheric testing of atomic bombs. Adoption of the LNT recommendation demonstrated extensive penetration of ideological influence affecting governmental, scientific and regulatory evaluation at the highest levels in the United States. This paper demonstrates that the scientific foundations for cancer risk assessment were inappropriately and inaccurately assessed, unethically adopted and require significant historical, scientific and regulatory remediation.

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Penicillium and Aspergillus are among the dominant genera of fungi in many environments. Exposure to these fungi may cause inflammation-related health effects, however the knowledge about this at species level is limited. The aim of this study was to obtain knowledge about cleaning workers' exposure to fungi and to investigate the total inflammatory potential (TIP) and the cytotoxic potential of fungal species. The fungi were obtained from the personal exposure of cleaning workers' in five nursing homes. In total 271 fungal isolates were identified using MALDI-TOF MS. The TIP and cytotoxic potential were determined for 30 different fungal isolates covering 17 species in an in vitro assay by exposing HL-60 cells to the fungal spores of each isolate. The geometric mean exposure of the cleaning workers was 351 CFU fungi/m3 air. We showed that the TIP and cytotoxicity varied among both species and isolates. At the two lowest doses, there was a positive relationship between spore concentration and TIP. The species with highest TIPs were A. candidus and P. italicum, while the most cytotoxic ones were A. niger and A. fumigatus. There was no obvious relationship between the TIP of an isolate and its cytotoxicity. The results of this study provide a better understanding of the inflammatory potential and cytotoxicity of different environmental fungal species and contribute to the risk evaluation of exposure to different Penicillium and Aspergillus species.

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The linear no-threshold (LNT) single-hit (SH) dose response model for cancer risk assessment is comprehensively assessed with respect to its historical foundations. This paper also examines how mistakes, ideological biases, and scientific misconduct by key scientists affected the acceptance, validity, and applications of the LNT model for cancer risk assessment. In addition, the analysis demonstrates that the LNT single-hit model was inappropriately adopted for governmental risk assessment, regulatory policy, practices, and for risk communication.

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Non-monotonic dose response curves (NMDRCs) occur in cells, tissues, animals and human populations in response to nutrients, vitamins, pharmacological compounds, hormones and endocrine disrupting chemicals (EDCs). Yet, regulatory agencies have argued that NMDRCs are not common, are not found for adverse outcomes, and are not relevant for regulation of EDCs. Under the linear dose response model, high dose testing is used to extrapolate to lower doses that are anticipated to be 'safe' for human exposures. NMDRCs that occur below the toxicological no-observed-adverse-effect level (NOAEL) would falsify a fundamental assumption, that high dose hazards can be used to predict low dose safety. In this commentary, we provide examples of NMDRCs and discuss how their presence in different portions of the dose response curve might affect regulatory decisions. We provide evidence that NMDRCs do occur below the NOAEL dose, and even below the 'safe' reference dose, for chemicals such as resveratrol, permethrin, chlorothalonil, and phthalates such as DEHP. We also briefly discuss the recent CLARITY-BPA study, which reported mammary adenocarcinomas only in rats exposed to the lowest BPA dose. We conclude our commentary with suggestions for how NMDRCs should be acknowledged and utilized to improve regulatory toxicity testing and in the calculation of reference doses that are public health protective.

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This paper summarizes the historical and scientific foundations of the Linear No-Threshold (LNT) cancer risk assessment model. The story of cancer risk assessment is an extraordinary one as it was based on an initial incorrect gene mutation interpretation of Muller, the application of this incorrect assumption in the derivation of the LNT single-hit model, and a series of actions by leading radiation geneticists during the 1946-1956 period, including a National Academy of Sciences (NAS) Biological Effects of Atomic Radiation (BEAR) I Genetics Panel (Anonymous, 1956), to sustain the LNT belief via a series of deliberate obfuscations, deceptions and misrepresentations that provided the basis of modern cancer risk assessment policy and practices. The reaffirming of the LNT model by a subsequent and highly influential NAS Biological Effects of Ionizing Radiation (BEIR) I Committee (NAS/NRC, 1972) using mouse data has now been found to be inappropriate based on the discovery of a significant documented error in the historical control group that led to incorrect estimations of risk in the low dose zone. Correction of this error by the original scientists and the application of the adjusted/corrected data back to the BEIR I (NAS/NRC, 1972) report indicates that the data would have supported a threshold rather than the LNT model. Thus, cancer risk assessment has a poorly appreciated, complex and seriously flawed history that has undermined policies and practices of regulatory agencies in the U.S. and worldwide to the present time.

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Prostate cancer is one of the leading causes of cancer-related mortality among men living in developed countries, making the development of safe, practical approaches to prostate cancer risk reduction a high research priority. The relationship between prostate cancer risk and selenium, an essential nutrient required for a number of metabolically important enzymes including glutathione peroxidases, has been investigated, but a satisfactory integration of results has proven elusive. Dogs, like men, naturally develop prostate cancer during aging, providing an appropriate context to study the effects of selenium supplementation on the dysregulation of homeostasis that drives cancer development within the aging prostate. In this paper, we summarize the translational significance of research results gained from dog studies on selenium and prostate cancer risk. Our discovery of a U-shaped dose-response between toenail selenium concentration and prostatic DNA damage in dogs remarkably parallels data on the relationship between selenium status and prostate cancer risk in men. Notably, the dog U-curve provides a plausible explanation for the unanticipated increase in prostate cancer incidence among men with highest baseline selenium who received selenium supplementation in the largest-ever prostate cancer prevention trial (SELECT). Moreover, the dog U-curve guided the discovery of a non-antioxidant, anti-carcinogenic mechanism of organic selenium - the preferential triggering of apoptosis in DNA damaged cells, which we have termed "homeostatic housecleaning". Taken together, the data from dogs and men indicate that increasing selenium status will not necessarily be associated with prostate cancer risk reduction. Landing in the trough of the U - achieving mid-range selenium status - is better than being too low or too high. Personalizing health promotion in a more-is-not-necessarily-better world poses distinctive challenges. Dog studies can be relied upon to contribute important insights into dose-dependent and form-dependent effects - two critical aspects of selenium biology that will have to be disentangled if the burgeoning science of selenium is to be translated into effective strategies for human disease prevention. Beyond contributing to understanding the role of selenium in biology, our work situates the concept of U-shaped thinking at the core of personalized medicine and precision nutrition.

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This paper assesses the discovery of the dose-rate effect in radiation genetics and how it challenged fundamental tenets of the linear non-threshold (LNT) dose response model, including the assumptions that all mutational damage is cumulative and irreversible and that the dose-response is linear at low doses. Newly uncovered historical information also describes how a key 1964 report by the International Commission for Radiological Protection (ICRP) addressed the effects of dose rate in the assessment of genetic risk. This unique story involves assessments by two leading radiation geneticists, Hermann J. Muller and William L. Russell, who independently argued that the report's Genetic Summary Section on dose rate was incorrect while simultaneously offering vastly different views as to what the report's summary should have contained. This paper reveals occurrences of scientific disagreements, how conflicts were resolved, which view(s) prevailed and why. During this process the Nobel Laureate, Muller, provided incorrect information to the ICRP in what appears to have been an attempt to manipulate the decision-making process and to prevent the dose-rate concept from being adopted into risk assessment practices.

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This paper reveals that nearly 25 years after the National Academy of Sciences (NAS), Biological Effects of Ionizing Radiation (BEIR) I Committee (1972) used Russell's dose-rate data to support the adoption of the linear-no-threshold (LNT) dose response model for genetic and cancer risk assessment, Russell acknowledged a significant under-reporting of the mutation rate of the historical control group. This error, which was unknown to BEIR I, had profound implications, leading it to incorrectly adopt the LNT model, which was a decision that profoundly changed the course of risk assessment for radiation and chemicals to the present.

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BACKGROUND: The association between serum selenium levels and type 2 diabetes mellitus (T2DM) is controversial. We performed a systematic review and non-linear dose-response meta-analysis of observational studies to investigate the association in the present study. METHODS: A comprehensive literature search was conducted using MEDLINE and EMBASE databases. A pooled odds ratio (OR) and related 95 % confidence interval (95 % CI) for T2DM between the highest and lowest serum selenium categories, and a non-linear dose-response relationship between selenium and T2DM were estimated. RESULTS: A total of five studies (of 13,460 participants) were identified as meeting the inclusion criteria. The pooled OR indicated that there was a significantly higher prevalence of T2DM in the highest category of blood selenium compared with the lowest (OR = 1.63, 95 % CI: 1.04-2.56, P = 0.033). Moreover, a significant non-linear dose-response relationship was observed between serum selenium levels and T2DM (P < 0.001). Serum selenium levels were positively associated with T2DM in populations with relatively low serum selenium levels (<97.5 µg/l) and those with high serum selenium levels (>132.5 µg/l). CONCLUSIONS: The positive association between serum selenium levels and T2DM existed in populations with relatively low levels and high levels of serum selenium, indicating a likely U-shaped non-linear dose-response relationship between serum selenium and T2DM.

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This paper provides a detailed rebuttal to the letter of Beyea (2016) which offered a series of alternative interpretations to those offered in my article in Environmental Research (Calabrese, 2015a) concerning the role of the U.S. National Academy of Sciences (NAS) Biological Effects of Atomic Radiation (BEAR) I Committee Genetics Panel in the adoption of the linear dose response model for cancer risk assessment. Significant newly uncovered evidence is presented which supports and extends the findings of Calabrese (2015a), reaffirming the conclusion that the Genetics Panel should be evaluated for scientific misconduct for deliberate misrepresentation of the research record in order to enhance an ideological agenda. This critique documents numerous factual errors along with extensive and deliberate filtering of information in the Beyea letter (2016) that leads to consistently incorrect conclusions and an invalid general perspective.

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