The (mis)use of ChatGPT in science and education: Turing, Djerassi, "athletics" & ethics.

ChatGPT is an amazing advance in technology, but it poses problems for teachers in universities and schools. How should use of ChatGPT by students be dealt with?

Before, During, and After the First Wave of COVID-19: Mortality Analyses Reveal Relevant Trends in Germany and its States until June 2020.

OBJECTIVE: Well-established mortality ratio methodology can contribute to a fuller picture of the SARS-CoV-2/COVID-19 burden of disease by revealing trends and informing mitigation strategies. This work examines respective data from Germany by way of example. METHODS: Using monthly and weekly all-cause mortality data from January 2016 to June 2020 (published by the German Federal Statistical Institute) for all ages,<65 years and≥65 years, and specified for Germany's federal states, we explored mortality as sequela of COVID-19. We analysed standardized mortality ratios (SMRs) comparing 2020 with 2016-2019 as reference years with a focus on trend detection. RESULTS: In Germany as a whole, elevated mortality in April (most pronounced for Bavaria) declined in May. The states of Hamburg and Bremen had increased SMRs in all months under study. In Mecklenburg-Western Pomerania, decreased SMRs in January turned monotonically to increased SMRs by June. Irrespective of age group, this trend was pronounced and significant. CONCLUSIONS: Increased SMRs in Hamburg and Bremen must be interpreted with caution because of potential upward distortions due to a "catchment bias". A pronounced excess mortality in April across Germany was confirmed and a hitherto undetected trend of increasing SMRs for Mecklenburg-Western Pomerania was revealed. To meet the pandemic challenge and to benefit from research based on data collected in standardized ways, national authorities should regularly conduct SMR analyses. For independent analyses, national authorities should also expedite publishing raw mortality and population data, including detailed information on age, sex, and cause of death, in the public domain.

Premature Deaths, Statistical Lives, and Years of Life Lost: Identification, Quantification, and Valuation of Mortality Risks.

Mortality effects of exposure to air pollution and other environmental hazards are often described by the estimated number of "premature" or "attributable" deaths and the economic value of a reduction in exposure as the product of an estimate of "statistical lives saved" and a "value per statistical life." These terms can be misleading because the number of deaths advanced by exposure cannot be determined from mortality data alone, whether from epidemiology or randomized trials (it is not statistically identified). The fraction of deaths "attributed" to exposure is conventionally derived as the hazard fraction (R - 1)/R, where R is the relative risk of mortality between high and low exposure levels. The fraction of deaths advanced by exposure (the "etiologic" fraction) can be substantially larger or smaller: it can be as large as one and as small as 1/e (≈0.37) times the hazard fraction (if the association is causal and zero otherwise). Recent literature reveals misunderstanding about these concepts. Total life years lost in a population due to exposure can be estimated but cannot be disaggregated by age or cause of death. Economic valuation of a change in exposure-related mortality risk to a population is not affected by inability to know the fraction of deaths that are etiologic. When individuals facing larger or smaller changes in mortality risk cannot be identified, the mean change in population hazard is sufficient for valuation; otherwise, the economic value can depend on the distribution of risk reductions.

[Deaths in nine regions of Italy in February/March 2020: "Mortality Excess Loupe" for SARS-CoV-2/COVID-19-Epidemiology in Germany]. / Todesfälle in neun Regionen Italiens im Februar/März 2020: "Mortalitäts-Exzess-Lupe" für SARS-CoV-2/COVID-19-Epidemiologie in Deutschland.

Italy is particularly affected by SARS-CoV-2/COVID-19. Recently, Colombo and Impicciatore compared the deaths in 1084 selected municipalities between 21 February 2020 and 21 March 2020 with deaths in the same time period in 2015 to 2019. We extend analyses of data from the Italian National Institute of Statistics (ISTAT) and calculate SMRs for all causes of death in the nine selected regions of Italy, separately for men and women and summarized. We analyze the effect of covariables by Poisson modelling and discuss the limitations of the current elaborations. We conclude: In agreement with Colombo and Impicciatore, in the particular corona situation, this "mortality excess loupe" - assuming otherwise constant determinants of death - can be a virus-test-independent tool to determine mortality effects of SARS-CoV-2. The current "loupe" is focused on municipalities with increases of more than 20% deaths in March 2020 compared to the average deaths on the same days in 2015-2019. The time window of investigation could be opened before 21 February 2020 to detect masked increases in mortality before the first "COVID-19 death" was ascertained. The current "loupe" conveys pronounced mortality increases also in regions that were not considered to be corona hotspots. In this respect, even in the absence of representative virus test results, mortality data can be important indicators of the distribution or spread of a newly acting factor. Overall, it is advisable to carry out SMR analyses for Germany on a regular basis, differentiated by region, gender, age group and cause of death. Such analyses can contribute to the early detection and evaluation of the severity of a deadly pandemic ("burden of disease") as well as to monitoring the dynamic spread of a factor such as SARS-CoV-2. SMR analyses can also be used to assess and evaluate both desired and undesired effects of measures taken against SARS-CoV-2/COVID-19 - and possibly other epidemics or pandemics.

[Why is the "Number of Premature Deaths Due to Environmental Exposures" not Appropriately Quantifiable?] / Warum ist die "Anzahl vorzeitiger Todesfälle durch Umweltexpositionen" nicht angemessen quantifizierbar?

Epidemiological studies and their applications in regulations of hazardous substances (e. g. by WHO, USA, EU) often quantify effects of environmental exposures on populations ("burden of disease") by calculating "numbers of premature deaths due to exposure". A recent example is the study by Schneider et al., commissioned by the German Federal Environmental Agency (Umweltbundesamt), into the burden of disease caused by exposures to nitrogen dioxide (NO2) in Germany. The authors assessed the proportion of premature deaths due to exposure by the "Attributable Fraction" (AF). However, true numbers of premature deaths caused by NO2 could be much higher or smaller. Indeed, Robins and Greenland showed in 1989 that the AF approach is inappropriate. Despite its far-reaching relevance for epidemiology and public health, their seminal work was not adequately taken into consideration, possibly due to its sophisticated level of mathematical argumentation. Our contribution illustrates - with simple examples - unappreciated but important pitfalls. We recommend that the concept of "number of premature deaths" be abandoned and "years of life lost due to exposure" be provided instead, calculated per capita. However, "years of life lost due to exposure" should not be stratified by age or causes of death (diseases). Furthermore, we show that "Disability Adjusted Life Years" (DALY) do not provide a meaningful measure to evaluate the effect of environmental exposures on populations.

Person-directed, non-pharmacological interventions for sleepiness at work and sleep disturbances caused by shift work.

BACKGROUND: Shift work is often associated with sleepiness and sleep disorders. Person-directed, non-pharmacological interventions may positively influence the impact of shift work on sleep, thereby improving workers' well-being, safety, and health. OBJECTIVES: To assess the effects of person-directed, non-pharmacological interventions for reducing sleepiness at work and improving the length and quality of sleep between shifts for shift workers. SEARCH METHODS: We searched CENTRAL, MEDLINE Ovid, Embase, Web of Knowledge, ProQuest, PsycINFO, OpenGrey, and OSH-UPDATE from inception to August 2015. We also screened reference lists and conference proceedings and searched the World Health Organization (WHO) Trial register. We contacted experts to obtain unpublished data. SELECTION CRITERIA: Randomised controlled trials (RCTs) (including cross-over designs) that investigated the effect of any person-directed, non-pharmacological intervention on sleepiness on-shift or sleep length and sleep quality off-shift in shift workers who also work nights. DATA COLLECTION AND ANALYSIS: At least two authors screened titles and abstracts for relevant studies, extracted data, and assessed risk of bias. We contacted authors to obtain missing information. We conducted meta-analyses when pooling of studies was possible. MAIN RESULTS: We included 17 relevant trials (with 556 review-relevant participants) which we categorised into three types of interventions: (1) various exposures to bright light (n = 10); (2) various opportunities for napping (n = 4); and (3) other interventions, such as physical exercise or sleep education (n = 3). In most instances, the studies were too heterogeneous to pool. Most of the comparisons yielded low to very low quality evidence. Only one comparison provided moderate quality evidence. Overall, the included studies' results were inconclusive. We present the results regarding sleepiness below. Bright light Combining two comparable studies (with 184 participants altogether) that investigated the effect of bright light during the night on sleepiness during a shift, revealed a mean reduction 0.83 score points of sleepiness (measured via the Stanford Sleepiness Scale (SSS) (95% confidence interval (CI) -1.3 to -0.36, very low quality evidence). Another trial did not find a significant difference in overall sleepiness on another sleepiness scale (16 participants, low quality evidence).Bright light during the night plus sunglasses at dawn did not significantly influence sleepiness compared to normal light (1 study, 17 participants, assessment via reaction time, very low quality evidence).Bright light during the day shift did not significantly reduce sleepiness during the day compared to normal light (1 trial, 61 participants, subjective assessment, low quality evidence) or compared to normal light plus placebo capsule (1 trial, 12 participants, assessment via reaction time, very low quality evidence). Napping during the night shiftA meta-analysis on a single nap opportunity and the effect on the mean reaction time as a surrogate for sleepiness, resulted in a 11.87 ms reduction (95% CI 31.94 to -8.2, very low quality evidence). Two other studies also reported statistically non-significant decreases in reaction time (1 study seven participants; 1 study 49 participants, very low quality evidence).A two-nap opportunity resulted in a statistically non-significant increase of sleepiness (subjective assessment) in one study (mean difference (MD) 2.32, 95% CI -24.74 to 29.38, 1 study, 15 participants, low quality evidence). Other interventionsPhysical exercise and sleep education interventions showed promise, but sufficient data to draw conclusions are lacking. AUTHORS' CONCLUSIONS: Given the methodological diversity of the included studies, in terms of interventions, settings, and assessment tools, their limited reporting and the very low to low quality of the evidence they present, it is not possible to determine whether shift workers' sleepiness can be reduced or if their sleep length or quality can be improved with these interventions.We need better and adequately powered RCTs of the effect of bright light, and naps, either on their own or together and other non-pharmacological interventions that also consider shift workers' chronobiology on the investigated sleep parameters.

Statistical considerations for a chronic bioassay study: Exposure to Decamethylcyclopentasiloxane (D5) and incidence of uterine endometrial adenocarcinomas in a 2-year inhalation study with Fischer rats.

Decamethylcyclopentasiloxane (D5) is a cyclic siloxane used in the production of industrial and consumer products. Four groups of 60 Fischer-344 female rats were analyzed for uterine endometrial adenocarcinoma (inhalation study with exposure levels in ppm/number of observed cases: 0/0, 10/1, 40/0, and 160/5) by exact regression (logistic, Poisson), the max poly-3 trend test, and a random effects probit model. When comparing the 160 ppm group to controls after 24 months, the incidence of adenocarcinomas was elevated (borderline significant); it was significant when all exposure levels were included. Four sets of (historical) control groups were formed, with varying heterogeneity. The effect of D5 was either significant or borderline significant when comparing all control sets to the 160 ppm group. When considering all exposure groups using any of the analysis methods, a significant effect was observed when the high dose group was included in the analysis; the effect was not significant when the high dose group was not included. The evidence tends to support the conclusion that D5 at the highest dose level (160 ppm) results in an increased incidence of adenocarcinomas. However, it is important to verify any potential effect through a biological investigation.

Translational toxicology in setting occupational exposure limits for dusts and hazard classification - a critical evaluation of a recent approach to translate dust overload findings from rats to humans.

BACKGROUND: We analyze the scientific basis and methodology used by the German MAK Commission in their recommendations for exposure limits and carcinogen classification of "granular biopersistent particles without known specific toxicity" (GBS). These recommendations are under review at the European Union level. We examine the scientific assumptions in an attempt to reproduce the results. MAK's human equivalent concentrations (HECs) are based on a particle mass and on a volumetric model in which results from rat inhalation studies are translated to derive occupational exposure limits (OELs) and a carcinogen classification. METHODS: We followed the methods as proposed by the MAK Commission and Pauluhn 2011. We also examined key assumptions in the metrics, such as surface area of the human lung, deposition fractions of inhaled dusts, human clearance rates; and risk of lung cancer among workers, presumed to have some potential for lung overload, the physiological condition in rats associated with an increase in lung cancer risk. RESULTS: The MAK recommendations on exposure limits for GBS have numerous incorrect assumptions that adversely affect the final results. The procedures to derive the respirable occupational exposure limit (OEL) could not be reproduced, a finding raising considerable scientific uncertainty about the reliability of the recommendations. Moreover, the scientific basis of using the rat model is confounded by the fact that rats and humans show different cellular responses to inhaled particles as demonstrated by bronchoalveolar lavage (BAL) studies in both species. CONCLUSION: Classifying all GBS as carcinogenic to humans based on rat inhalation studies in which lung overload leads to chronic inflammation and cancer is inappropriate. Studies of workers, who have been exposed to relevant levels of dust, have not indicated an increase in lung cancer risk. Using the methods proposed by the MAK, we were unable to reproduce the OEL for GBS recommended by the Commission, but identified substantial errors in the models. Considerable shortcomings in the use of lung surface area, clearance rates, deposition fractions; as well as using the mass and volumetric metrics as opposed to the particle surface area metric limit the scientific reliability of the proposed GBS OEL and carcinogen classification.

Wind turbines and health: An examination of a proposed case definition.

Renewable energy demands have increased the need for new wind farms. In turn, concerns have been raised about potential adverse health effects on nearby residents. A case definition has been proposed to diagnose "Adverse Health Effects in the Environs of Industrial Wind Turbines" (AHE/IWT); initially in 2011 and then with an update in 2014. The authors invited commentary and in turn, we assessed its scientific merits by quantitatively evaluating its proposed application. We used binomial coefficients to quantitatively assess the potential of obtaining a diagnosis of AHE/IWT. We also reviewed the methodology and process of the development of the case definition by contrasting it with guidelines on case definition criteria of the USA Institute of Medicine. The case definition allows at least 3,264 and up to 400,000 possibilities for meeting second- and third-order criteria, once the limited first-order criteria are met. IOM guidelines for clinical case definitions were not followed. The case definition has virtually no specificity and lacks scientific support from peer-reviewed literature. If applied as proposed, its application will lead to substantial potential for false-positive assessments and missed diagnoses. Virtually any new illness that develops or any prevalent illness that worsens after the installation of wind turbines within 10 km of a residence could be considered AHE/IWT if the patient feels better away from home. The use of this case definition in the absence of a thorough medical evaluation with appropriate diagnostic studies poses risks to patients in that treatable disorders would be overlooked. The case definition has significant potential to mislead patients and its use cannot be recommended for application in any health-care or decision-making setting.

Lowest adverse effects concentrations (LOAECs) for formaldehyde exposure.

In 2012 the Committee for Risk Assessment (RAC) of the European Chemicals Agency concluded that 2ppm formaldehyde represent a Lowest Observed Adverse Effect Concentration (LOAEC) for polypoid adenomas, histopathological lesions and cell proliferation. An analysis of all data shows that a LOAEC of 2ppm it is not justified for cell proliferation and polypoid adenomas. Higher values are also supported by a new statistical analysis. For histopathological lesions a NOAEC of 1ppm may be defined but the lesions at 2ppm cannot be regarded as pre-stages for tumour development. One major uncertainty exists: the description of polypoid adenomas and the lesions at 2ppm often is insufficient and diagnostic uncertainties can only be resolved by a re-evaluation according to modern histomorphological standards. Although the discrepancy between our assessment and that of RAC may seem rather small we feel the LOAECs proposed by RAC must be challenged taking into consideration the broad data base for formaldehyde and the potential impact of any published RAC opinion on the present discussions about appropriate occupational and indoor exposure limits.

Circadian epidemiology: Structuring circadian causes of disease and practical implications.

That disruptions of the body's internal clockwork can lead to negative health consequences, including cancer, is a plausible hypothesis. Yet, despite strong mechanistic and animal support, the International Agency for Research on Cancer (IARC) experts considered epidemiological evidence as limited regarding the carcinogenicity of "shift-work involving circadian disruption" (2007) and "night shift work" (2019). We use directed acyclic graphs (DAGs) to outline a concept of circadian causes that discloses challenges when choosing appropriate exposure variables. On this basis, we propose to move beyond shift-work alone as a direct cause of disease. Instead, quantifying chronodisruption as individual doses can lead to interpretable circadian epidemiology. The hypothesis is that doses of chronodisruption cause disrupted circadian organisation by leading to desynchronization of circadian rhythms. Chronodisruption can be conceptualized as the split physiological nexus of internal and external times. Biological (or internal) night - an individual's intrinsically favoured sleep time window - could be the backbone of circadian epidemiology. In practice, individual doses that cause disrupted circadian organisation are derived from the intersection of time intervals of being awake and an individual's biological night. After numerous studies counted work shifts, chronobiology may now advance circadian epidemiology with more specific dose estimation - albeit with greater challenges in measurement (time-dependent individual data) and analysis (time-dependent confounding).

Daylight Saving Time Transitions and Risk of Heart Attack­a Systematic Review and Meta-Analysis.

BACKGROUND: The health risks of daylight saving time transitions are intensely debated. Disturbed circadian rhythms and lack of sleep after transitions might increase the risk of acute myocardial infarction (AMI). The only meta-analysis on the risk of AMI has now been considerably expanded. METHODS: In this systematic review and meta-analysis (including meta-regressions and sensitivity analyses), we examine the frequency of AMI in the first few weeks after daylight saving time transitions (OSF registration www.doi.org/10.17605/OSF.IO/7CFKS). Eight databases were searched for pertinent literature up to September 2023. Authors were contacted for additional information. Study quality was rated using the Newcastle-Ottawa Scale. RESULTS: Twelve studies from ten countries were included in the meta-analysis. Nine were of adequate quality, and three were of good quality. The pooled relative risk (RR) of AMI after daylight saving time onset (spring) was 1.04 (95% confidence interval [1.02; 1.07], I2: 57.3%), and 1.02 ([0.99; 1.05], I2: 51.6%) after daylight saving time offset (autumn). Recalculation after the exclusion of one study with inconsistencies yielded pooled RR values of 1.04 [1.01; 1.06] and 1.00 [0.99; 1.02], with the spring results being heterogeneous (I2: 56.9%) and the autumn results homogeneous (I2: 17.1%). CONCLUSION: Current evidence suggests that there may be an increased risk of AMI after the spring transition, although there is moderate to marked heterogeneity among the studies that support this conclusion. More easily interpretable studies, such as those already conducted in the field of economics, should clarify associations with the aid of discontinuity regression and placebo tests. To this end, comparative risk analyses using years or places wherein daylight saving time was not practiced would be suitable.