Dose-response Model Research Articles

Asbestos exposure and asbestosis mortality in Italian cement-asbestos cohorts: Dose-response relationship and the role of competing death causes.

In Italy, asbestos was used intensively until its ban in 1992, which was extended for asbestos cement factories until 1994. The aim of this study was to evaluate the dose-response between asbestos exposure and asbestosis mortality across a pool of Italian occupational cohorts, taking into account the presence of competing risks. Cohorts were followed for vital status and the cause of death was ascertained by a linkage with mortality registers. Cause-specific (CS) Cox-regression models were used to evaluate the dose-exposure relationship between asbestosis mortality and the time-dependent cumulative exposure index (CEI) to asbestos. Fine and Gray regression models were computed to assess the effect of competing risks of death. The cohort included 12,963 asbestos cement workers. During the follow-up period (1960-2012), of a total of 6961 deaths, we observed 416 deaths attributed to asbestosis, 879 to lung cancer, 400 to primary pleural cancer, 135 to peritoneal cancer, and 1825 to diseases of the circulatory system. The CS model showed a strong association between CEI and asbestosis mortality. Dose-response models estimated an increasing trend in mortality even below a CEI of 25 ff/mL-years. Lung cancer and circulatory diseases were the main competing causes of death. Asbestos exposure among Italian asbestos-cement workers has led to a very high number of deaths from asbestosis and asbestos-related diseases. The increasing risk trend associated with excess deaths, even at low exposure levels, suggests that the proposed limit values would not have been adequate to prevent disability and mortality from asbestosis.

Differential Functional Changes in Visual Performance during Acute Exposure to Microgravity Analogue and Their Potential Links with Spaceflight-Associated Neuro-Ocular Syndrome.

Spaceflight-Associated Neuro-Ocular Syndrome (SANS) is a complex pathology threatening the health of astronauts, with incompletely understood causes and no current specific functional diagnostic or screening test. We investigated the use of the differential performance of the visual system (central vs. perimacular visual function) as a candidate marker of SANS-related pathology in a ground-based microgravity analogue. We used a simple reaction time (SRT) task to visual stimuli, presented in the central and perimacular field of view, as a measure of the overall performance of the visual function, during acute settings (first 10 min) of vertical, bed rest (BR), -6°, and -15° head-down tilt (HDT) presentations in healthy participants (n = 8). We built dose-response models linking the gravitational component to SRT distribution parameters in the central vs. perimacular areas. Acute exposure to microgravity induces detectable changes between SRT distributions in the perimacular vs. central retina (increased mean, standard deviation, and tau component of the ex-Gaussian function) in HDT compared with vertical presentation. Functional testing of the perimacular retina might be beneficial for the earlier detection of SANS-related ailments in addition to regular testing of the central vision. Future diagnostic tests should consider the investigation of the extra-macular areas, particularly towards the optic disc.

Parallel explorations in LA-NSCLC: Chemoradiation dose-response optimisation considering immunotherapy and cardiac toxicity sparing

Background and purposeChemoradiotherapy (CRT) for locally-advanced non-small cell lung cancer (LA-NSCLC) has undergone advances, including increased overall survival (OS) when combined with immune checkpoint blockade (ICB), and using cardiac-sparing techniques to reduce the radiotoxicity. This research investigated 1) how radiotherapy schedules can be optimised with CRT-ICB schemes, and 2) how cardiac-sparing might change the OS for concurrent CRT (cCRT). Methods and materialsSurvival data and dosimetric indices were sourced from published studies, with 2-year OS standardised and the hazard ratio of mean heart dose (MHD) against radiotoxicity tabulated in purpose. A published CRT dose–response model was selected, then modified with ICB and cardiac-sparing hypotheses. Models were maximum likelihood fitted, then visualised the prediction outcomes after bootstrapping. ResultsThe modelled 2-year OS rate of cCRT-ICB reached 71 % (95 % confidence intervals, CI 62 %, 84 %) and 66 % (95 % CI: 53 %, 81 %) for stage IIIA and IIIB/C, respectively, given 60 Gy in 2 Gy-per-fraction. 60 Gy in 30 fractions remained the best schedule for cCRT-ICB, whereas modest dose de-escalation to 55 Gy only reduced the OS in 2 %. Sequential CRT (sCRT)-ICB provided 6 % OS increases versus the best OS rate achieved by sCRT alone. Photon MHD-sparing achieved a 5–10 % increase in modelled 2-year OS, with protons providing a further roughly 5–10 % increase. ConclusionNeither dose-escalation nor de-escalation relative to 60 Gy in 30 fractions influenced the survival with cCRT-ICB, while 5 Gy dose de-escalation might benefit patients with heavily irradiated organs at risk. Cardiac-sparing improved OS, and protons provided advantages for tumours anatomically overlapped or lay below the heart.

Efficient Study Design and Analysis of Longitudinal Dose-Response Data Using Fractional Polynomials.

Correctly characterising the dose-response relationship and taking the correct dose forward for further study is a critical part of the drug development process. We use optimal design theory to compare different designs and show that using longitudinal data from all available timepoints in a continuous-time dose-response model can substantially increase the efficiency of estimation of the dose-response compared to a single timepoint model. We give theoretical results to calculate the efficiency gains for a large class of these models. For example, a linearly growing Emax dose-response in a population with a between/within-patient variance ratio ranging from 0.1 to 1 measured at six visits can be estimated with between 1.43 and 2.22 times relative efficiency gain, or equivalently, with 30% to a 55% reduced sample size, compared to a single model of the final timepoint. Fractional polynomials are a flexible way to incorporate data from repeated measurements, increasing precision without imposing strong constraints. Longitudinal dose-response models using two fractional polynomial terms are robust to mis-specification of the true longitudinal process while maintaining, often large, efficiency gains. These models have applications for characterising the dose-response at interim or final analyses.

Machine learning for the adsorptive removal of ciprofloxacin using sugarcane bagasse as a low-cost biosorbent: comparison of analytic, mechanistic, and neural network modeling.

Contamination with traces of pharmaceutical compounds, such as ciprofloxacin, has prompted interest in their removal via low-cost, efficient biomass-based adsorption. In this study, classical models, a mechanistic model, and a neural network model were evaluated for predicting ciprofloxacin breakthrough curves in both laboratory- and pilot scales. For the laboratory-scale (d = 2.2cm, Co = 5mg/L, Q = 7mL/min, T = 18°C) and pilot-scale (D = 4.4cm, Co = 5mg/L, Q = 28mL/min, T = 18°C) setups, the experimental adsorption capacities were 2.19 and 2.53mg/g, respectively. The mechanistic model reproduced the breakthrough data with high accuracy on both scales (R2 > 0.4 and X2 < 0.15), and its fit was higher than conventional analytical models, namely the Clark, Modified Dose-Response, and Bohart-Adams models. The neural network model showed the highest level of agreement between predicted and experimental data with values of R2 = 0.993, X2 = 0.0032 (pilot-scale) and R2 = 0.986, X2 = 0.0022 (laboratory-scale). This study demonstrates that machine learning algorithms exhibit great potential for predicting the liquid adsorption of emerging pollutants in fixed bed.

Quantitative Microbial Risk Assessment of Antibiotic-Resistant E. coli, Legionella pneumophila, and Mycobacteria in Nonpotable Wastewater Reuse Applications.

Antibiotic-resistant bacteria (ARB) have become a major threat to public health and modern medicine. A simple death kinetics-based dose-response model (SD-DRM) was incorporated into a quantitative microbial risk assessment (QMRA) to assess the risks of exposure to reclaimed wastewater harboring antibiotic-resistant E. coli, Legionella pneumophila, and Mycobacterium avium for multiple exposure scenarios. The fractions of ARB and trace antibiotics present in the body were incorporated to demonstrate their impact on infection risks. Both ARB and antibiotic susceptible bacteria, ASB, are assumed to have the same dose-response in the absence of antibiotics but behave differently in the presence of residual antibiotics in the body. Annual risk of L. pneumophila infection exceeded the EPA 10-4 pppy (per person per year) benchmark at concentrations in reclaimed water greater than 103-104 CFU/L, depending on parameter variation. Enteropathogenic E. coli infection risks meet the EPA annual benchmark at concentrations around 105-106 total E. coli. The results illustrated that an increase in residual antibiotics from 0 to 40% of the minimum inhibitory concentration (MIC) reduced the risk by about 1 order of magnitude for E. coli but was more likely to result in an untreatable infection.

Secondary cancer risk in six anatomical sites when using PAT, IMPT, and VMAT/IMRT radiotherapy

Background and purposeCompared to intensity modulated proton therapy (IMPT), proton arc therapy (PAT) is expected to improve dose conformality, delivery efficiency, and provide a more favorable LET distribution. Alternatively, the low-dose bath is potentially spread over larger volumes, which could impact the likelihood of developing a radiation-induced, secondary cancer (SC). The goal of this study was to evaluate this risk in several anatomical sites using newly developed commercial tools. Materials and methodsTreatment plans encompassing six anatomical sites, five patients per site, and three techniques per patient were created using RayStation. Techniques included PAT and IMPT for protons, and either volumetrically modulated radiotherapy (VMAT) or intensity modulated radiotherapy (IMRT) for photons. Risk estimates were based on the organ-equivalent dose (OED) concept using both Schneider’s mechanistic dose–response model for carcinoma induction and a linear dose–response model. ResultsWith few exceptions, mean and integral dose were lowest with PAT. For protons, the factor OEDIMPT/OEDPAT ranged from 0.7 to 1.8 with both the mechanistic and linear model, while for photons OEDphoton/OEDPAT ranged from 1.5 to 10 using the mechanistic model and 1.3 to using the linear model. A strong correlation was found between mean dose and OED for organs with significant repopulation/repair (high R value) and less cell death from single hit interactions (low α value). ConclusionBased on results from both mechanistic and linear risk models, the transition from IMPT to PAT should not substantially affect SC risk in patients treated with proton therapy. Additionally, when using Schneider’s model, the shapes of the dose–response curves can be used as a good predictor of how SC risk will respond to shifts from intermediate dose to low dose as anticipated when moving from IMPT to PAT.

Salmonella Prevalence in Raw Cocoa Beans and a Microbiological Risk Assessment to Evaluate the Impact of Cocoa Liquor Processing on the Reduction of Salmonella

Salmonella in raw cocoa beans (n = 870) from main sourcing areas over nine months was analyzed. It was detected in 71 (ca. 8.2%) samples, with a contamination level of 0.3–46 MPN/g except for one sample (4.1 × 104 CFU/g). Using prevalence and concentration data as input, the impact of thermal treatment in cocoa processing on the risk estimate of acquiring salmonellosis by a random Belgian chocolate consumer was calculated by a quantitative microbiological risk assessment (QMRA) approach. A modular process risk model from raw cocoa beans to cocoa liquor up to a hypothetical final product (70–90% dark chocolate tablet) was set up to understand changes in Salmonella concentrations following the production process. Different thermal treatments during bean or nib steam, nib roasting, or liquor sterilization (achieving a 0–6 log reduction of Salmonella) were simulated. Based on the generic FAO/WHO Salmonella dose–response model and the chocolate consumption data in Belgium, salmonellosis risk per serving and cases per year at population level were estimated. When a 5 log reduction of Salmonella was achieved, the estimated mean risk per serving was 3.35 × 10−8 (95% CI: 3.27 × 10−10–1.59 × 10−7), and estimated salmonellosis cases per year (11.7 million population) was 88 (95% CI: <1–418). The estimated mean risk per serving was 3.35 × 10−9 (95% CI: 3.27 × 10−11–1.59 × 10−8), and the estimated salmonellosis cases per year was 9 (95% CI: <1–42), for a 6 log reduction. The current QMRA model solely considered Salmonella reduction in a single-step thermal treatment in the cocoa process. Inactivation obtained during other process steps (e.g. grinding) might occur but was not considered. As the purpose was to use QMRA as a tool to evaluate the log reduction in the cocoa processing, no postcontamination from the processing environment and ingredients was included. A minimum of 5 log reduction of Salmonella in the single-step thermal treatment of cocoa process was considered to be adequate.

Scientific Committee guidance on appraising and integrating evidence from epidemiological studies for use in EFSA's scientific assessments.

EFSA requested its Scientific Committee to prepare a guidance document on appraising and integrating evidence from epidemiological studies for use in EFSA's scientific assessments. The guidance document provides an introduction to epidemiological studies and illustrates the typical biases, which may be present in different epidemiological study designs. It then describes key epidemiological concepts relevant for evidence appraisal. This includes brief explanations for measures of association, exposure assessment, statistical inference, systematic error and effect modification. The guidance then describes the concept of external validity and the principles of appraising epidemiological studies. The customisation of the study appraisal process is explained including tailoring of tools for assessing the risk of bias (RoB). Several examples of appraising experimental and observational studies using a RoB tool are annexed to the document to illustrate the application of the approach. The latter part of this guidance focuses on different steps of evidence integration, first within and then across different streams of evidence. With respect to risk characterisation, the guidance considers how evidence from human epidemiological studies can be used in dose-response modelling with several different options being presented. Finally, the guidance addresses the application of uncertainty factors in risk characterisation when using evidence from human epidemiological studies.

Guidance on risk-benefit assessment of foods.

The EFSA Scientific Committee has updated its 2010 Guidance on risk-benefit assessment (RBA) of foods. The update addresses methodological developments and regulatory needs. While it retains the stepwise RBA approach, it provides additional methods for complex assessments, such as multiple chemical hazards and all relevant health effects impacting different population subgroups. The updated guidance includes approaches for systematic identification, prioritisation and selection of hazardous and beneficial food components. It also offers updates relevant to characterising adverse and beneficial effects, such as measures of effect size and dose-response modelling. The guidance expands options for characterising risks and benefits, incorporating variability, uncertainty, severity categorisation and ranking of different (beneficial or adverse) effects. The impact of different types of health effects is assessed qualitatively or quantitatively, depending on the problem formulation, scope of the RBA question and data availability. The integration of risks and benefits often involves value-based judgements and should ideally be performed with the risk-benefit manager. Metrics such as Disability-Adjusted Life Years (DALYs) and Quality-Adjusted Life Years (QALYs) can be used. Additional approaches are presented, such as probability of all relevant effects and/or effects of given severities and their integration using severity weight functions. The update includes practical guidance on reporting results, interpreting outcomes and communicating the outcome of an RBA, considering consumer perspectives and responses to advice.

On modelling airborne infection risk.

Airborne infection risk analysis is usually performed for enclosed spaces where susceptible individuals are exposed to infectious airborne respiratory droplets by inhalation. It is usually based on exponential, dose-response models of which a widely used variant is the Wells-Riley (WR) model. We revisit this infection-risk estimate and extend it to the population level. We use an epidemiological model where the mode of pathogen transmission, airborne or contact, is explicitly considered. We illustrate the link between epidemiological models and the WR and the Gammaitoni and Nucci models. We argue that airborne infection quanta are, up to an overall density, airborne infectious respiratory droplets modified by a parameter that depends on biological properties of the pathogen, physical properties of the droplet and behavioural properties of the individual. We calculate the time-dependent risk of being infected for two scenarios. We show how the epidemic infection risk depends on the viral latent period and the event time, the time infection occurs. Infection risk follows the dynamics of the infected population. As the latent period decreases, infection risk increases. The longer a susceptible is present in the epidemic, the higher its risk of infection for equal exposure time to the pathogen is.

Semi-parametric benchmark dose analysis with monotone additive models.

Benchmark dose analysis aims to estimate the level of exposure to a toxin associated with a clinically significant adverse outcome and quantifies uncertainty using the lower limit of a confidence interval for this level. We develop a novel framework for benchmark dose analysis based on monotone additive dose-response models. We first introduce a flexible approach for fitting monotone additive models via penalized B-splines and Laplace-approximate marginal likelihood. A reflective Newton method is then developed that employs de Boor's algorithm for computing splines and their derivatives for efficient estimation of the benchmark dose. Finally, we develop a novel approach for calculating benchmark dose lower limits based on an approximate pivot for the nonlinear equationsolved by the estimated benchmark dose. The favorable properties of this approach compared to the Delta method and a parameteric bootstrap are discussed. We apply the new methods to make inferences about the level of prenatal alcohol exposure associated with clinically significant cognitive defects in children using data from six NIH-funded longitudinal cohort studies. Software to reproduce the results in this paper is available online and makes use of the novel semibmd R package, which implements the methods in this paper.

How Much Physical Activity Is Needed for 75 Year and Older Adults: Using NHANES Datasets

&amp;lt;i&amp;gt;Targets&amp;lt;/i&amp;gt;: To examine the amount/level of Physical Activity (PA) needed to generate the most health benefits in noninstitutionalized 75 year and older U.S. resident adults. Intervention description: A total of 598 sample participants aged 75 year and above from National Health And Nutrition Examination Survey (NHANES) 2005-2006 datasets were included. Actigraph-monitored daily step counts, self-reported PA duration (time spent in weekly PA) and weekly energy expenditure were used to describe PA level/amount. Functional ability was expressed using the total levels of difficulties in doing twenty-one types of daily activities. PRISM Dose-response Curves Stimulation Variable slope model was applied to examine the needed PA level/amount in the population. &amp;lt;i&amp;gt;Mechanisms of action&amp;lt;/i&amp;gt;: PA benefits functional health in 75 year and older adults. Older females aged 75- 84 year need at least 150 mins/ 800 kcal energy expenditure per week or 5,800 daily steps to reach the most functional benefits. Older men aged 75-84 year need walk about 5,800 steps/day to achieve higher level of functionality. Older adults aged 85 years and above need to spend about 240 minutes/week on PA to gain health benefits. &amp;lt;i&amp;gt;Outcomes&amp;lt;/i&amp;gt;: Older males generally need/engage in more amount of PA compared to their female counterparts. Between 75-84 year old male and female adults, PA intensity is more important/reflective in male for expressing PA amount, while time spent in PA is more meaningful to older females. There is no difference in needed PA amount between different genders in 85 year and older adults.

Association between thyroid function and nonalcoholic fatty liver disease: a dose-response meta-analysis.

Thyroid hormones (THs) have been found that it is closely associated with the onset and progression of non-alcoholic fatty liver disease (NAFLD). However, the current study could not verify the intrinsic relationship between thyroid hormones and NAFLD, which requires further research. The searches of studies reported both TH level in serum and NAFLD were performed in PubMed, Web of Science, Cochrane Library, and Embase databases. We combined an overall meta-analysis with a dose-response meta-analysis to assess the correlation and dose-response relationship between thyroid function levels and the risk of NAFLD. Overall, 10 studies were included with a total of 38,425 individuals. We found that the non-linear dose-response model showed that for every 1 ng/dL increase in FT4, the risk of NAFLD was reduced by 10.56% (p=0.003). The odds ratios (ORs) for NAFLD with high free triiodothyronine (FT3) exposure compared to those with low FT3 were 1.580 (95% CI 1.370 to 1.830, I2=0.0%, p<0.001) in the overall meta-analysis. The continuous variable meta-analysis indicated that individuals with high levels of TSH (SMD=1.32, 95% CI 0.660 to 1.970, p<0.001) had significantly higher levels of liver fibrosis than those with low levels. Our findings only validate that there is a correlation between the occurrence of NAFLD and abnormal levels of THs, and it is expected that more observational studies will still be conducted in the future to further demonstrate the relationship between thyroid hormones and NAFLD. Registered number in PROSPERO: CRD42023405052.

A New Training Load Quantification Method at Supramaximal Intensity and Its Application in Injuries Among Members of an International Volleyball Team.

Bouzigues, T, Maurelli, O, Imbach, F, Prioux, J, and Candau, R. A new training load quantification method at supramaximal intensity and its application in injuries among members of an international volleyball team. J Strength Cond Res 38(8): 1453-1463, 2024-The quantification of training loads (TLs) is essential for optimizing jump performance and reducing the occurrence of injuries. This study aimed to (a) propose a new method for quantifying TLs in explosive exercises, (b) determine the nature of the relationship between TLs dynamics and injury occurrence, and (c) assess a TL critical for training schedule purposes, above which the risk of injury occurrence becomes unacceptable. This study was conducted with 11 male volleyball players on a national team during a 5-month international competitive period. The proposed new method for quantifying TLs is based on a weighting factor applied to relative jumping intensities, determined by the number of sustainable jumps and their intensities measured by G-Vert accelerometer. The relationship between TLs dynamics and injury occurrence was assessed using a variable dose-response model. A high coefficient of determination was found between the maximum number of jumps possible and their intensities ( r2 = 0.94 ± 0.14, p < 0.001), indicating a strong physiological relationship between jumping intensities and the constraints imposed. The occurrence of injury was dependent on TLs dynamics for 2 players ( r2 = 0.26 ± 0.01; p < 0.001). The TL critical corresponded to 11 jumps over 80% of maximum jump height during games and approximately 130 jumps at <80% of maximal jump height. The present study proposes a new approach for quantifying supramaximal exercises and provides tools for training schedules and the prevention of volleyball injuries.

Efficacy and safety of eliapixant in endometriosis-associated pelvic pain: the randomized, placebo-controlled phase 2b SCHUMANN study

BackgroundThe SCHUMANN study evaluated the efficacy and safety of the selective P2 × 3 antagonist eliapixant in patients with endometriosis-associated pelvic pain (EAPP).MethodsSCHUMANN was a randomized, placebo- and active comparator-controlled, double-blind to placebo and open-label to comparator, parallel-group, multicenter, dose-finding phase 2b study. The participants were women with surgically diagnosed endometriosis who fulfilled defined EAPP criteria. Participants were randomized 1:1:1:1 to twice daily (BID) 25 mg, 75 mg, or 150 mg oral eliapixant or a placebo for 12 weeks. An exploratory once-daily elagolix 150 mg treatment group was also included. The primary endpoint was the absolute change in mean worst EAPP from baseline to the end of intervention (EOI).ResultsOverall, 215 participants were randomized for treatment (44 to eliapixant 25 mg, 44 to eliapixant 75 mg, 43 to eliapixant 150 mg, 43 to a placebo, and 41 to elagolix 150 mg). For safety reasons, the study was terminated early; both treatment and enrollment stopped immediately, producing less than 50% of the planned number of completers. The study found no significant differences in EAPP reduction from baseline between groups and no significant dose-response model. The elagolix 150 mg group showed better pain reduction than any of the other groups. No new safety signals were observed, relative to the previously known safety profile of eliapixant, which was generally well tolerated. However, one case of moderate and probably drug-induced liver injury in a participant receiving eliapixant 150 mg BID supported the association between eliapixant and a potential increase in liver function values, defined before the start of the phase 2 program.ConclusionsThis study did not meet its primary objective as no statistically significant or clinically relevant differences in changes of mean worst EAPP from baseline were observed between treatment groups. The single observed case of moderate, probably drug-induced liver injury was the second case in the eliapixant phase 2 program conducted in the following indications: refractory or unexplained chronic cough, diabetic neuropathic pain, overactive bladder, and EAPP. Due to this, the benefit-risk ratio for the study was no longer considered to be positive.Clinical trial registrationClinicalTrials.gov identifier NCT04614246; registered November 3, 2020.

Association between obstructive sleep apnea severity and depression risk: a systematic review and dose-response meta-analysis.

Obstructive sleep apnea (OSA) has received considerable attention as a potential risk factor for depressive symptoms. The systematic review was conducted to confirm the dose‒response connection between OSA severity and depression risk. A systematic literature search of English and Chinese articles published in PubMed, EMBASE, Scopus, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), and SinoMed databases from their inception to 28 August 2023 was conducted. An evaluation using the Newcastle‒Ottawa Scale was performed. A meta-analysis was used to evaluate the impact of OSA severity. A random-effects dose‒response model was conducted to evaluate the linear and nonlinear dose‒response connections. We evaluated publication bias by funnel plots, and symmetry by Egger's test. We identified 18 cross-sectional researches. 3143 participants which were involved in the dose‒response meta-analysis. Contrasted with mild OSA, individuals with severe OSA had a higher adjusted risk of depression (rate ratio: 1.34, 95% confidence interval = 1.05-1.70), with substantial heterogeneity (I2 = 70.9%, Pheterogeneity<0.001). There is a significant linear connection between OSA severity and depression risk. The depression risk increased by 0.4% for every 1 event per hour increase in the apnea-hypopnea index (AHI). The protocol for this unfunded research was drafted and registered at PROSPERO (ID CRD42023474097).

Parametric analysis of SARS-CoV-2 dose-response models in transportation scenarios.

Transportation systems involve high-density crowds of geographically diverse people with variations in susceptibility; therefore, they play a large role in the spread of infectious diseases like SARS-CoV-2. Dose-response models are widely used to model the relationship between the trigger of a disease and the level of exposure in transmission scenarios. In this study, we quantified and bounded viral exposure-related parameters using empirical data from five transportation-related events of SARS-CoV-2 transmission. Dose-response models were then applied to parametrically analyze the infection spread in generic transportation systems, including a single-aisle airplane, bus, and railway coach, and then examined the mitigating efficiency of masks by performing a sensitivity analysis of the related factors. We found that dose level significantly affected the number of secondary infections. In general, we observed that mask usage reduced infection rates at all dose levels and that high-quality masks equivalent to FFP2/N95 masks are effective for all dose levels. In comparison, we found that lower-quality masks exhibit limited mitigation efficiency, especially in the presence of high dosage. The sensitivity analysis indicated that a reduction in the infection distance threshold is a critical factor in mask usage.

Loss of coral thermotolerance following year-long in situ nursery propagation with a consecutively high summer heat-load

Exposure to more frequent ocean warming events is driving the loss of coral reef cover as the window of recovery between episodes of bleaching reduces. Coral propagation via in situ nurseries and subsequent outplanting have increased worldwide to support replenishing coral cover on degraded reefs. However, challenges in identifying fast-growing and bleaching-resistant target corals have limited how informative we can be regarding the resilience of outplanted corals. Here, we employed short-term thermal stress assays using the Coral Bleaching Automated Stress System (CBASS) to assess the thermal threshold of a fast-growing coral pre- and post-propagation on in situ nursery frames. We show that year-long nursery-propagated corals exhibit a statistically significant reduction in thermal thresholds (i.e., ED50s) compared to their corresponding reef-based donor colonies based on dose–response modelling of dark acclimated photosynthetic efficiency. RNA-Seq was then used to assess the underlying drivers of this thermotolerance reduction, identifying that processes involved in metabolic and oxidative stress management were disrupted in nursery versus donor heat-treated corals. Whether trade-offs during potential growth-focused phases (post-fragmentation), nursery conditions, and/or a consecutively high summer heat-load drove the lower thermal capacity remains to be determined. However, nursery corals expressed genes associated with telomere maintenance, which are typically expressed in stress-sensitive fast-growing corals under seasonal environmental stress, suggesting consecutively high summer heat-loading contributed to the observed patterns. Our results highlight that thermal tolerance is (i) variable and (ii) subject to acclimation to varying degrees across colonies. Thus, a path forward for reef practitioners to improve propagation efforts may entail the initial screening of a larger reef population from which thermally superior colonies can be selected for propagation.

Metabolomics Simultaneously Derives Benchmark Dose Estimates and Discovers Metabolic Biotransformations in a Rat Bioassay.

Benchmark dose (BMD) modeling estimates the dose of a chemical that causes a perturbation from baseline. Transcriptional BMDs have been shown to be relatively consistent with apical end point BMDs, opening the door to using molecular BMDs to derive human health-based guidance values for chemical exposure. Metabolomics measures the responses of small-molecule endogenous metabolites to chemical exposure, complementing transcriptomics by characterizing downstream molecular phenotypes that are more closely associated with apical end points. The aim of this study was to apply BMD modeling to in vivo metabolomics data, to compare metabolic BMDs to both transcriptional and apical end point BMDs. This builds upon our previous application of transcriptomics and BMD modeling to a 5-day rat study of triphenyl phosphate (TPhP), applying metabolomics to the same archived tissues. Specifically, liver from rats exposed to five doses of TPhP was investigated using liquid chromatography-mass spectrometry and 1H nuclear magnetic resonance spectroscopy-based metabolomics. Following the application of BMDExpress2 software, 2903 endogenous metabolic features yielded viable dose-response models, confirming a perturbation to the liver metabolome. Metabolic BMD estimates were similarly sensitive to transcriptional BMDs, and more sensitive than both clinical chemistry and apical end point BMDs. Pathway analysis of the multiomics data sets revealed a major effect of TPhP exposure on cholesterol (and downstream) pathways, consistent with clinical chemistry measurements. Additionally, the transcriptomics data indicated that TPhP activated xenobiotic metabolism pathways, which was confirmed by using the underexploited capability of metabolomics to detect xenobiotic-related compounds. Eleven biotransformation products of TPhP were discovered, and their levels were highly correlated with multiple xenobiotic metabolism genes. This work provides a case study showing how metabolomics and transcriptomics can estimate mechanistically anchored points-of-departure. Furthermore, the study demonstrates how metabolomics can also discover biotransformation products, which could be of value within a regulatory setting, for example, as an enhancement of OECD Test Guideline 417 (toxicokinetics).