Credible Interval Research Articles

Temperature, relative humidity and elderly type 2 diabetes mortality: A spatiotemporal analysis in Shandong, China

BackgroundThe mortality of type 2 diabetes mellitus (T2DM) can be affected by environmental factors. However, few studies have explored the effects of environmental factors across diverse regions over time. Given the vulnerability observed in the elderly group in previous research, this research applied Bayesian spatiotemporal models to assess the associations in the elderly group. MethodsData on T2DM death in the elderly group (aged over 60 years old) at the county level were collected from the National Death Surveillance System between 1st January 2013 and 31st December 2019 in Shandong Province, China. A Bayesian spatiotemporal model was employed with the integrated Nested Laplace Approach to explore the associations between socio-environmental factors (i.e., temperatures, relative humidity, the Normalized Difference Vegetation Index (NDVI), particulate matter with a diameter of 2.5 μm or less (PM2.5) and gross domestic product (GDP)) and T2DM mortality. ResultsT2DM mortality in the elderly group was found to be associated with temperature and relative humidity (i.e., temperature: Relative Risk (RR) = 1.41, 95% Credible Interval (CI): 1.27–1.56; relative humidity: RR = 1.05, 95% CI:1.03–1.06), while no significant associations were found with NDVI, PM2.5 and GDP. In winter, significant impacts from temperature (RR = 1.18, 95% CI: 1.06–1.32) and relative humidity (RR = 0.94, 95% CI: 0.89–0.99) were found. Structured and unstructured spatial effects, temporal trends and space-time interactions were considered in the model. ConclusionsHigher mean temperatures and relative humidities increased the risk of elderly T2DM mortality in Shandong Province. However, a higher humidity level decreased the T2DM mortality risk in winter in Shandong Province. This research indicated that the spatiotemporal method could be a useful tool to assess the impact of socio-environmental factors on health by combining the spatial and temporal effects.

Effect of spirulina on risk of hospitalization among patients with COVID-19: the TOGETHER randomized trial

BackgroundAlgae-derived nutraceuticals, such as spirulina, have been reported to have biological activities that may minimize clinical consequences to COVID-19 infections. ObjectivesThis study aimed to determine whether spirulina is an effective treatment for high-risk patients with early COVID-19 in an outpatient setting. MethodsThe TOGETHER trial is a placebo-controlled, randomized, platform trial conducted in Brazil. Eligible participants were symptomatic adults with a positive rapid test for SARS-CoV-2 older than 50 y or with a known risk factor for disease severity. Patients were randomly assigned to receive placebo or spirulina (1 g twice daily for 14 d). The primary end point was hospitalization defined as either retention in a COVID-19 emergency setting for >6 h or transfer to tertiary hospital owing to COVID-19 at 28 d. Secondary outcomes included time-to-hospitalization, mortality, and adverse drug reactions. We used a Bayesian framework to compare spirulina with placebo. ResultsWe recruited 1126 participants, 569 randomly assigned to spirulina and 557 to placebo. The median age was 49.0 y, and 65.3% were female. The primary outcome occurred in 11.2% in the spirulina group and 8.1% in the placebo group (odds ratio [OR]: 1.24; 95% credible interval: 0.84, 1.86). There were no differences in emergency department visit (OR: 1.21; 95% credible interval: 0.81, 1.83), nor time to symptom relief (hazard ratio: 0.90; 95% credible interval: 0.79, 1.03). Spirulina also not demonstrate important treatment effects in the prespecified subgroups defined by age, sex, BMI, days since symptom onset, or vaccination status. ConclusionsSpirulina has no any clinical benefits as an outpatient therapy for COVID-19 compared with placebo with respect to reducing the retention in an emergency setting or COVID-19–related hospitalization. There are no differences between spirulina and placebo for other secondary outcomes.This trial was registered at clinicaltrials.gov as NCT04727424.

An early giant planet instability recorded in asteroidal meteorites

Giant planet migration appears widespread among planetary systems in our Galaxy. However, the timescales of this process, which reflect the underlying dynamical mechanisms, are not well constrained, even within the Solar System. As planetary migration scatters smaller bodies onto intersecting orbits, it would have resulted in an epoch of enhanced bombardment in the Solar System’s asteroid belt. Here, to accurately and precisely quantify the timescales of migration, we interrogate thermochronologic data from asteroidal meteorites, which record the thermal imprint of energetic collisions. We present a database of 40K–40Ar system ages from chondrite meteorites and evaluate it with an asteroid-scale thermal code coupled to a Markov chain Monte Carlo inversion. Simulations require bombardment to reproduce the observed age distribution and identify a bombardment event beginning 11.3−6.6+9.5Myr\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$11.{3}_{-6.6}^{+9.5}\\, {\\mathrm{Myr}}$$\\end{document} after the Sun formed (50% credible interval). Our results associate a giant planet instability in our Solar System with the dissipation of the gaseous protoplanetary disk.

The application of the Bayesian linear regression model to optimize the maintenance of a programmable logic controller

In this paper, an optimization approach, which is based on the Bayesian Linear Inference (BLI) model, has been proposed for the maintenance of Programmable Logic Controllers (PLCs). The BLI model, which is implemented using historical data, incorporates maintenance indicators like the number of failures (NF), total downtime (TD), total unexpected intervals (TUI), mean time to repair (MTTR) and mean time between failures (MTBF). It offers a probabilistic framework for determining the influence of each predictor variable on PLC maintenance. The model produces posterior means, credible intervals, and standard deviations, which provide insights into the magnitude and uncertainty of these relationships. The results from the study show that factors like NF and TD are influenced by the magnitude and direction of the maintenance levels. Also, the R-squared score (0.85) also indicates how much of the variability in maintenance in the system. From the results obtained, the study can conclude that the BLI model can optimize PLC maintenance procedures by identifying essential components and their contributions. Also, it is able to estimate future maintenance requirements and helps with resource allocation and process optimization decisions.

Exploring age-related changes in motor function: insights from the peak decline found in Koji Awareness screening test

The KOJI AWARENESS (KA) screening test assesses motor function in humans. We aimed to analyze the correlation between age and KA screening scores and to identify the specific age at which a significant decline occurs. A total of 793 healthy participants (234 females) were interviewed for basic information on age and sex and completed the KA screening test. In addition to calculating the total score from the KA test, the scores were calculated for the neck-scapula-upper extremity-complex (NSU), trunk, and lower extremity (LE) segments. Spearman’s rank correlation coefficient was used to assess the validity of the test. Additionally, Bayesian linear regression was employed to estimate the change point in KA scores, facilitating the identification of a critical age associated with a notable decline in motor function. KA screening total and separate body segment scores were negatively correlated with age in both gender (for female and male, KA total score, ρ = − 0.443, ρ = − 0.344; NSU segment, ρ = − 0.431, ρ = − 0.427; trunk segment, ρ = − 0.210, ρ = − 0.473; LE segment: ρ = − 0.43, ρ = − 0.507). Furthermore, a change-point analysis using linear regression analysis showed that KA screening total scores declined sharply at the age of 49.1(95% credible interval: 37.503, 68.366). The result show that total KA scores decrease − 0.196 (95% credible interval: − 0.335, − 0.049) for every 1 year of age increase, and for ages over 49.1, total KA scores additionally decrease − 0.255 (95% credible interval: − 0.485, − 0.054) for every 1 year of age increase. In the NSU segment, females showed a more rapid decline than males from the age of 50 years. KA screening test total scores declined sharply at the age of 49.1. These results may be useful in setting treatment goals, exercise, and lifestyle programs for age-related decline in motor function.

Practical parameter identifiability and handling of censored data with Bayesian inference in mathematical tumour models

Mechanistic mathematical models (MMs) are a powerful tool to help us understand and predict the dynamics of tumour growth under various conditions. In this work, we use 5 MMs with an increasing number of parameters to explore how certain (often overlooked) decisions in estimating parameters from data of experimental tumour growth affect the outcome of the analysis. In particular, we propose a framework for including tumour volume measurements that fall outside the upper and lower limits of detection, which are normally discarded. We demonstrate how excluding censored data results in an overestimation of the initial tumour volume and the MM-predicted tumour volumes prior to the first measurements, and an underestimation of the carrying capacity and the MM-predicted tumour volumes beyond the latest measurable time points. We show in which way the choice of prior for the MM parameters can impact the posterior distributions, and illustrate that reporting the most likely parameters and their 95% credible interval can lead to confusing or misleading interpretations. We hope this work will encourage others to carefully consider choices made in parameter estimation and to adopt the approaches we put forward herein.

The Influence of Nutrition Intervention on the P1NP and CTX-1 Response to an Acute Exercise Bout: A Systematic Review with Meta-Analysis.

Although nutrition and exercise both influence bone metabolism, little is currently known abouttheir interaction, or whether nutritional intervention can modulate the bone biomarker response to acute exercise. Improved understanding of the relationships between nutrition, exercise and bone metabolism may have substantial potential to inform nutritional interventions to protect the bone health of exercising individuals, and to elucidate mechanisms by which exercise and nutrition influence bone. The aim was to synthesise available evidence related to the influence of nutrition on the response of the bone biomarkers procollagen type 1 N-terminal propeptide (P1NP) and C-terminal telopeptide of type 1 collagen (CTX-1) to acute exercise, using a systematic review and meta-analytic approach. Studies evaluating the influence of nutritional status or intervention on the bone biomarker response to an acute exercise bout were included and separated into four categories: (1) feeding status and energy availability, (2) macronutrients, (3) micronutrients and (4) other. Studies conducted on healthy human populations of any age or training status were included. Meta-analysis was conducted when data from at least five studies with independent datasets were available. In the case of insufficient data to warrant meta-analysis, results from individual studies were narratively synthesised and standardised mean effect sizes visually represented. Twenty-two articles were included. Of these, three investigated feeding status or energy availability, eight macronutrients, eight micronutrients (all calcium) and six other interventions including dairy products or collagen supplementation. Three studies had more than one intervention and were included in all relevant outcomes. The largest and most commonly reported effects were for the bone resorption marker CTX-1. Meta-analysis indicated that calcium intake, whether provided via supplements, diet or infusion, reduced exercise-induced increases in CTX-1 (effect size - 1.1; 95% credible interval [CrI] - 2.2 to - 0.05), with substantially larger effects observed in studies that delivered calcium via direct infusion versus in supplements or foods. Narrative synthesis suggests that carbohydrate supplementation may support bone during acute exercise, via reducing exercise-induced increases in CTX-1. Conversely, a low-carbohydrate/high-fat diet appears to induce the opposite effect, as evidenced by an increased exercise associated CTX-1 response, and reduced P1NP response. Low energy availability may amplify the CTX-1 response to exercise, but it is unclear whether this is directly attributable to energy availability or to the lack of specific nutrients, such as carbohydrate. Nutritional intervention can modulate the acute bone biomarker response to exercise, which primarily manifests as an increase in bone resorption. Ensuring adequate attention to nutritional factors may be important to protect bone health of exercising individuals, with energy, carbohydrate and calcium availability particularly important to consider. Although a wide breadth of data were availablefor this evidence synthesis, there was substantial heterogeneity in relation to design and intervention characteristics. Direct and indirect replication is required to confirm key findings and to generate better estimates of true effect sizes.

Impact of cerebral protection on observed versus predicted in-hospital stroke in a high stroke risk TAVR cohort

BackgroundDespite impressive improvements in the safety profile of Transcatheter aortic valve replacement (TAVR), the risk for peri-procedural stroke after TAVR has not declined substantially. In an effort to reduce periprocedural stroke, cerebral embolic protection (CEP) devices have been utilized but have yet to demonstrate benefit in all-comers. There is a paucity of data supporting the utilization of CEP in TAVR patients with an anticipated high risk for peri-procedural stroke.MethodsThe Transcatheter Aortic Valve Replacement In-Hospital Stroke (TASK) score is a clinical risk tool for predicting the in-hospital stroke risk of patients undergoing transfemoral TAVR. This score was used to identify high-risk patients and calculate the expected in-hospital stroke risk. This was a single-centre cohort study in all consecutive TAVR patients who had placement of CEP. The observed versus expected ratio for peri-procedural stroke was calculated. To obtain 95% credible intervals, we used 1000 bootstrapped samples of the original cohort sample size without replacement and recalculated the TASK predicted scores.ResultsThe study included 103 patients. The median age was 83 (IQR 78,89). 63 were male (61.1%) and 45 (43.69%) had a history of previous Stroke or TIA. Two patients had an in-hospital stroke after TAVR (1.94%). The expected risk of in-hospital stroke based on the TASK score was 3.39% (95% CI 3.07–3.73). The observed versus expected ratio was 0.57 (95% CI 0.52–0.64).ConclusionIn this single-center study, we found that in patients undergoing TAVR with high stroke risk, CEP reduced the in-hospital stroke risk by 43% when compared with the risk-score predicted rate.Clinical trial numberN/A.

Linking Opinions Shared on Social Media About COVID-19 Public Health Measures to Adherence: Repeated Cross-Sectional Surveys of Twitter Use in Canada.

The effectiveness of public health measures (PHMs) depends on population adherence. Social media were suggested as a tool to assess adherence, but representativeness and accuracy issues have been raised. The objectives of this repeated cross-sectional study were to compare self-reported PHM adherence and sociodemographic characteristics between people who used Twitter (subsequently rebranded X) and people who did not use Twitter. Repeated Canada-wide web-based surveys were conducted every 14 days from September 2020 to March 2022. Weighted proportions were calculated for descriptive variables. Using Bayesian logistic regression models, we investigated associations between Twitter use, as well as opinions in tweets, and self-reported adherence with mask wearing and vaccination. Data from 40,230 respondents were analyzed. As self-reported, Twitter was used by 20.6% (95% CI 20.1%-21.2%) of Canadians, of whom 29.9% (95% CI 28.6%-31.3%) tweeted about COVID-19. The sociodemographic characteristics differed across categories of Twitter use and opinions. Overall, 11% (95% CI 10.6%-11.3%) of Canadians reported poor adherence to mask-wearing, and 10.8% (95% CI 10.4%-11.2%) to vaccination. Twitter users who tweeted about COVID-19 reported poorer adherence to mask wearing than nonusers, which was modified by the age of the respondents and their geographical region (odds ratio [OR] 0.79, 95% Bayesian credibility interval [BCI] 0.18-1.69 to OR 4.83, 95% BCI 3.13-6.86). The odds of poor adherence to vaccination of Twitter users who tweeted about COVID-19 were greater than those of nonusers (OR 1.76, 95% BCI 1.48-2.07). English- and French-speaking Twitter users who tweeted critically of PHMs were more likely (OR 4.07, 95% BCI 3.38-4.80 and OR 7.31, 95% BCI 4.26-11.03, respectively) to report poor adherence to mask wearing than non-Twitter users, and those who tweeted in support were less likely (OR 0.47, 95% BCI 0.31-0.64 and OR 0.96, 95% BCI 0.18-2.33, respectively) to report poor adherence to mask wearing than non-Twitter users. The OR of poor adherence to vaccination for those tweeting critically about PHMs and for those tweeting in support of PHMs were 4.10 (95% BCI 3.40-4.85) and 0.20 (95% BCI 0.10-0.32), respectively, compared to non-Twitter users. Opinions shared on Twitter can be useful to public health authorities, as they are associated with adherence to PHMs. However, the sociodemographics of social media users do not represent the general population, calling for caution when using tweets to assess general population-level behaviors.

The influence of water and air temperature on elite wheelchair triathlon performance

ABSTRACT Impaired thermoregulatory function is a clinical feature of many health conditions that affect triathletes using wheelchairs and consequently, individual athlete performances may fluctuate according to environmental temperature. We aimed to determine the effect of 1) water temperature on wheelchair triathlon swim time, and 2) air temperature on handcycle and wheelchair run (push) time. Published race records from 2017 to 2023 (n = 49events) were extracted from the World Triathlon website. Bayesian negative binomial regression was used to separately model the nonlinear relationships between water temperature and swim time, and air temperature and handcycle and push time. Age, sex, sport class, whether wetsuits were worn (swim model) and swim time (handcycle and push model) were included as fixed effects. Over the observed water temperature range of 15.7–30.5°C, male swim time (mm:ss) improved from 14:13 min (95% credible interval [CrI] = 12:27, 16:09) to 12:35 min (95% CrI = 11:00, 14:19). Female swim time improved from 15:33 min (95% CrI = 13:24, 17:55) to 12:46 min (95% CrI = 11:03, 14:38). It was unclear whether handcycle and push time slowed over the observed air temperature range of 14–33°C. Warmer water temperatures, up to 30.5°C, were associated with faster swim times. It was unclear whether combined handcycle and push time slowed with increases in air temperature, up to 33°C. The integration of information on athlete impairment type and severity with performance data is needed to better understand the extent to which individual athlete performances fluctuate across environmental conditions.

Phylogenetic relationships and historical biogeography of silkmoths (Lepidoptera: Bombycidae) suggest an origin in Southern Gondwana

Silkmoths (Bombycidae) have a disjunct distribution predominantly in the Southern Hemisphere and Asia. Here we reconstruct the phylogenetic history of the family to test competing hypotheses on their origin and assess how vicariance and long-distance dispersal shaped their current distribution. We sequenced up to 5,074 base pairs from six loci (COI, EF1-α, wgl, CAD, GAPDH, and RpS5) to infer the historical biogeography of Bombycidae. The multilocus dataset covering 20 genera (80 %) of the family, including 17 genera (94 %) of Bombycinae and 3 genera (43 %) of Epiinae, was used to estimate phylogenetic patterns, divergence times and biogeographic reconstruction. Dating estimates extrapolated from secondary calibration sources indicate the Bombycidae stem-group originated approximately 64 Mya. The subfamilies Epiinae (South America) and Bombycinae (Australia, Asia, East Palaearctic, and Africa) were reciprocally monophyletic, diverging at c. 56 Mya (95 % credibility interval: 66–46 Mya). The ‘basal’ lineage of Bombycinae — Gastridiota + Elachyophtalma — split from the rest of Bombycinae c. 53 Mya (95 % credibility interval: 63–43 Mya). Gastridiota is a monobasic genus with a relictual distribution in subtropical forests of eastern Australia. The Oriental and African genera comprised a monophyletic group: the Oriental region was inferred to have been colonized from a long-distance dispersal event from Australia to South-East Asia c. 53 Mya or possibly later (c. 36–26 Mya); Africa was subsequently colonized by dispersal from Asia c. 16 Mya (95 % credibility interval: 21–12 Mya). Based on the strongly supported phylogenetic relationships and estimates of divergence times, we conclude that Bombycidae had its origin in the fragment of Southern Gondwana consisting of Australia, Antarctica and South America during the Paleocene. The disjunction between South America (Epiinae) and Australia (Bombycinae) is best explained by vicariance in the Eocene, whereas the disjunct distribution in Asia and Africa is best explained by more recent dispersal events.

Neighborhood Disadvantage and Prostate Tumor Aggressiveness among African American and European American Men.

Studies have identified associations between neighborhood disadvantage (ND), which is more likely to affect African American (AA) individuals, and aggressive prostate cancer. Thus, ND may contribute to prostate cancer disparities. However, it is unknown what ND components drive aggressive disease and whether associations vary by race. We evaluated associations between aggressive prostate cancer and four ND metrics-Area Deprivation Index (ADI), validated Bayesian Neighborhood Deprivation Index (NDI), racial isolation (RI) index, and historical redlining, and whether these factors interacted with race, among men with prostate cancer treated at the University of Maryland Greenebaum Comprehensive Cancer Center (2004-2021). We included 1,458 men (698 European American and 760 AA). AA men were more likely to experience ND. In adjusted models, the ADI, RI, and redlining were significantly associated with aggressive versus nonaggressive prostate cancer overall [ADI, OR for one SD increase = 1.14, 95% confidence interval (CI), 1.00-1.30; RI, OR = 1.27, CI, 1.07-1.51; redlining, OR = 1.77; CI, 1.23-2.56] and among AA men. The NDI was associated with aggressive prostate cancer among AA men (OR = 1.32, 95% credible interval: 1.13-1.57); percent in poverty received the largest importance weight. The ADI (P heterogeneity = 0.002) and NDI (exceedance probability heterogeneity = 98.1%) significantly interacted with race, such that associations were significantly stronger for AA men. We identified novel significant positive associations for racial segregation and historical redlining with aggressive prostate cancer and significant interactions between ND indices and race. Findings inform specific ND components that are associated with aggressive prostate cancer and suggest the ND effect is stronger for AA men, which has implications for interventions to reduce disparities.

Proof of principle X-ray reflection mass measurement of the black hole in H1743−322

ABSTRACT The black hole X-ray binary H1743−322 lies in a region of the Galaxy with high extinction, and therefore it has not been possible to make a dynamical mass measurement. In this paper, we make use of a recent model which uses the X-ray reflection spectrum to constrain the ratio of the black hole mass to the source distance. By folding in a reported distance measurement, we are able to estimate the mass of the black hole to be $12\pm 2~\text{M}_\odot {}$ ($1\sigma$ credible interval). We are then able to revise a previous disc continuum fitting estimate of black hole spin $a_*$ (previously relying on a population mass distribution) using our new mass constraint, finding $a_*=0.47\pm 0.10$. This work is a proof of principle demonstration of the method, showing it can be used to find the mass of black holes in X-ray binaries.

The impact of winning funding on researcher productivity, results from a randomized trial

Abstract The return on investment of funding science has rarely been accurately measured. Previous estimates of the benefits of funding have used observational studies, including regression discontinuity designs. In 2013, the Health Research Council of New Zealand began awarding funding using a modified lottery, with an initial peer review stage followed by funding at random for short-listed applicants. This allowed us to compare research outputs between those awarded funding or not using a randomized experimental study design. The analysis included eighty-eight researchers who were followed for an average of 3.8 years of follow-up. The rate ratios (and 95 per cent credible intervals (CI)) for funding were 0.95 (95 per cent CI 0.67 to 1.39) for publications and 1.06 (95 per cent CI 0.79 to 1.43) for citations, showing no clear impact of funding on research outputs. The wider use of funding lotteries could provide robust estimates of the benefits of research funding to better inform science policy.

Comparison of Different Doses of Oral and Ocular Propranolol for Retinopathy of Prematurity: A Network Meta-Analysis.

The efficacy and safety of propranolol for retinopathy of prematurity (ROP) remain under debate. This network meta-analysis (NMA) focuses on whether a ranking may be established for different dose levels of propranolol as treatment of ROP in terms of stage progression as the primary outcome, with appearance of plus disease and need for anti-vascular endothelial growth factors (anti-VEGFs) or laser therapy as secondary endpoints. Fourteen studies (10 randomised controlled trials, three single-arm trials and one retrospective observational study) of 474 patients treated with oral or ocular propranolol were retrieved from databases up to April 2024. Meta-insight and model-based NMA were undertaken to evaluate the propranolol dose-response relationship. Studies were evaluated for model fit, risk of bias and Confidence of evidence In Network Meta-Analysis (CINeMA). Effect sizes were determined as odds ratio (OR) with 95% credible interval (CrI). Bayesian analysis showed a trend towards improved effects for propranolol given at late stages (stages 2-3; S23) of ROP progression compared with its administration at earlier stages (stages 0-1; S01). OR values for oral propranolol 1.5 and 2mg/kg/day given at S23 were 0.13 (95% CrI 0.04-0.37) and 0.16 (95% CrI 0.04-0.61), respectively, while given at S01 were 0.28 (95% CrI 0.02-2.96) and 0.78 (95% CrI 0.14-4.43), respectively. Similarly, OR of eye propranolol 0.2% at S23 was 0.37 (95% CrI 0.09-1.00) versus an S01 OR of 0.64 (95% CrI 0.21-2.04). Surface under the cumulative ranking curve (SUCRA) analyses confirmed best probability values for oral propranolol 1.5-2mg/kg followed by eye propranolol 0.2%, all at S23. Model-based NMA showed nonlinearity in the dose-response for oral propranolol with a trend to greater maximal effect for its administration at late versus early stages. For secondary endpoints, lower risk values were found with oral propranolol 1.5mg/kg/day at S23 for progression to plus disease (OR 0.14; 95% CrI 0.02-0.84) and need for anti-VEGFs (OR 0.23; 95% CrI 0.05-0.93) and laser (OR 0.16; 95% CrI 0.02-1.10) therapies also followed by eye propranolol 0.2%, and a similar profile was obtained with SUCRA analysis. Lower doses (0.5-1.0mg/kg/day) of oral propranolol retained efficacy. Threat of adverse events was estimated as risk difference versus control with no difference for eye propranolol 0.2% and oral propranolol 0.5mg/kg/day, modest increases of risk for oral propranolol 1.0 and 1.5mg/kg/day and the highest risk difference for oral propranolol 2.0mg/kg/day (0.06; 95% CI -0.01 to 0.13). A diminished risk of disease progression and need for additional treatment was obtained with propranolol in ROP, but safety is a potential concern. Propranolol eye micro-drops (0.2%) can be as efficacious as oral propranolol. Nonetheless, the evidence is limited due to the paucity and quality of the available studies.

ICU patients receiving remifentanil do not experience reduced duration of mechanical ventilation: a systematic review of randomized controlled trials and network meta-analyses based on Bayesian theories.

The purpose of this network meta-analysis (NMA) was to evaluate the efficacy of intravenous opioid μ-receptor analgesics in shortening the duration of mechanical ventilation (MV) in ICU patients. Randomized controlled trials comparing the efficacy of remifentanil, sufentanil, morphine, and fentanyl on the duration of MV in ICU patients were searched in Embase, Cochrane, Pubmed, and Web of Science electronic databases. The primary outcome was MV duration. The Bayesian random-effects framework was used to evaluate relative efficacy. In total 20 studies were included in this NMA involving 3,442 patients. Remifentanil was not associated with a reduction in the duration of MV compared with fentanyl (mean difference (MD) -0.16; 95% credible interval (CrI): -4.75 ~ 5.63) and morphine (MD 3.84; 95% CrI: -0.29 ~ 10.68). The secondary outcomes showed that, compared with remifentanil, sufentanil can prolong the duration of extubation. No regimen significantly shortened the ICU length of stay and improved the ICU mortality, efficacy, safety, and drug-related adverse events. Among these analgesics, remifentanil did not appear to be associated with a reduction in MV duration. Clinicians should carefully titrate the analgesia of MV patients to prevent a potentially prolonged duration of MV due to excessive or inadequate analgesic therapy. https://www.crd.york.ac.uk/prospero/, CRD42021232604.

Mixtures of Urinary Phenol and Phthalate Metabolite Concentrations in Relation to Serum Lipid Levels among Pregnant Women: Results from the EARTH Study.

We examined whether mixtures of urinary concentrations of bisphenol A (BPA), parabens and phthalate metabolites were associated with serum lipid levels among 175 pregnant women who enrolled in the Environment and Reproductive Health (EARTH) Study (2005-2017), including triglycerides, total cholesterol, high-density lipoprotein (HDL), non-HDL, and low-density lipoprotein (LDL). We applied Bayesian Kernel Machine Regression (BKMR) and quantile g-computation while adjusting for confounders. In the BKMR models, we found no associations between chemical mixture and lipid levels, e.g., total cholesterol [mean difference (95% CRI, credible interval) = 0.02 (-0.31, 0.34)] and LDL [mean difference (95% CRI) = 0.10 (-0.22, 0.43)], when comparing concentrations at the 75th to the 25th percentile. When stratified by BMI, we found suggestive positive relationships between urinary propylparaben and total cholesterol and LDL among women with high BMI [mean difference (95% CRI) = 0.25 (-0.26, 0.75) and 0.35 (-0.25, 0.95)], but not with low BMI [mean difference (95% CRI) = 0.00 (-0.06, 0.07) and 0.00 (-0.07, 0.07)]. No association was found by quantile g-computation. This exploratory study suggests mixtures of phenol and phthalate metabolites were not associated with serum lipid levels during pregnancy, while there were some suggestive associations for certain BMI subgroups. Larger longitudinal studies with multiple assessments of both exposure and outcome are needed to corroborate these novel findings.

A Bayesian bias-adjusted random-effects model for synthesizing evidence from randomized controlled trials and nonrandomized studies of interventions.

An important consideration when combining RCTs and NRSIs is how to address their potential biases in the pooled estimates. This study aimed to propose a Bayesian bias-adjusted random effects model for the synthesis of evidence from RCTs and NRSIs. We present a Bayesian bias-adjusted random effects model based on power prior method, which combines the likelihood contribution of the NRSIs, raised to the power parameter of alpha, with the likelihood of the RCT data, modeled with an additive bias. The method was illustrated using a meta-analysis on the association between low-dose methotrexate exposure and melanoma. We also combined RCTs and NRSIs using the naïve data synthesis. The results including only RCTs has a posterior median and 95% credible interval (CrI) of 1.18 (0.31-4.04), the posterior probability of any harm (>1.0) and a meaningful association (>1.15) were 0.61 and 0.52, respectively. The posterior median and 95% CrI based on the naïve data synthesis resulted in 1.17 (0.96-1.47), and the posterior probability of any harm and a meaningful association were 0.96 and 0.60, respectively. For the Bayesian bias-adjusted analysis, the median OR was 1.16 (95% CrI: 0.83-1.71), and the posterior probabilities of any and a meaningful clinical association were 0.88 and 0.53, respectively. The results indicated that integrating NRSIs into meta-analysis could increase the certainty of the body of evidence. However, directly combining RCTs and NRSIs in the same meta-analysis without distinction may lead to misleading conclusions.

Site-specific cancer mortality after low level exposure to ionizing radiation: Findings from an update of the International Nuclear Workers Study (INWORKS).

A major update to the International Nuclear Workers Study was undertaken that allows us to report updated estimates of associations between radiation and site-specific solid cancer mortality. A cohort of 309,932 nuclear workers employed in France, the United Kingdom, and United States were monitored for external radiation exposure and associations with cancer mortality were quantified as the excess relative rate (ERR) per gray (Gy) using a maximum likelihood and a Markov chain Monte Carlo method (to stabilize estimates via a hierarchical regression). The analysis included 28,089 deaths due to solid cancer, the most common being lung, prostate, and colon cancer. Using maximum likelihood, positive estimates of ERR per Gy were obtained for stomach, colon, rectum, pancreas, peritoneum, larynx, lung, pleura/mesothelioma, bone and connective tissue, skin, prostate, testis, bladder, kidney, thyroid, and residual cancers; negative estimates of ERR per Gy were found cancers of oral cavity and pharynx, esophagus, and ovary. A hierarchical model stabilized site-specific estimates of association, including for lung (ERR per Gy=0.65; 95% credible interval [CrI]: 0.24, 1.07), prostate (ERR per Gy=0.44; 95% CrI: -0.06, 0.91), and colon cancer (ERR per Gy=0.53; 95% CrI: -0.07, 1.11). The results contribute evidence regarding associations between low dose radiation and cancer.

Application of computer vision and machine learning in morphological characterization of Adansonia digitata fruits

Measuring fruit mass and volume is a time-consuming and tedious task that can affect production planning. This study developed a computer vision system to estimate the volume and mass of baobab fruits from single-view images captured from inexpensive and readily available cameras such as those in smartphones. The baobab fruits were collected from two study fields within the savanna ecological zone. Their images were captured, and subsequently, they were detected and segmented with over 97 % accuracy. The segmented images were binarized, and two-dimensional (2D) features such as the segmented area, centroid, bounding box, equivalent diameter, and major diameter were extracted from them. The volumes of the fruits were estimated from the 2D features using random forest, linear, polynomial, and radial support vector machine models. All the models achieved high goodness of fit; however, the random forest model delivered the best performance, with an R2 value of 99.8 %. The relationship between mass and volume was a quadratic equation (mass = 38.23 + 0.25 × volume + 4.49e−05 × volume2) and had an R2 value of 92 %. Correlations were validated via plots and statistical tests, and credible intervals of point estimates were determined from the posterior distributions of their samples. This highlights the potential of artificial intelligence methods to be applied in a less constrained environmental setting for ecological research and agricultural management. Commercial companies producing baobab powder and seed oil should apply these models for effective production planning. To enhance the model, it would be beneficial to gain a better understanding of how climate gradients affect the morphological characteristics of baobab fruits.