Bayesian modeling

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively...

INTRODUCTION: Studies have compared chimeric antigen receptor (CAR) T-cell therapies and salvage chemotherapy in relapsed/refractory large B-cell lymphoma (LBCL) patients, but further evidence of their relative effectiveness is warranted. METHODS: Our systematic review identified studies comparing efficacy and safety outcomes of axicabtagene ciloleucel (axi-cel), lisocabtagene maraleucel (liso-cel) and tisagenlecleucel (tisa-cel) trials to salvage chemotherapy cohorts in LBCL patients with ≥ 2 prior lines of treatment; and an extended evidence network included indirect comparisons comparing CAR T-cell therapies...

Low-cost air pollution sensors, offering hyper-local characterization of pollutant concentrations, are becoming increasingly prevalent in environmental and public health research. However, low-cost air pollution data can be noisy, biased by environmental conditions, and usually need to be field-calibrated by collocating low-cost sensors with reference-grade instruments. We show, theoretically and empirically, that the common procedure of regression-based calibration using collocated data systematically underestimates high air pollution concentrations, which are critical to diagnose from a health perspective...

The objectives of this herd-level prospective observational cohort study were to describe the proportion of cows with elevated prepartum nonesterified fatty acid concentrations (PropElevNEFA) in dairy herds and to assess the herd-level associations between PropElevNEFA and postpartum diseases, reproductive performance, and culling. From November 2018 to December 2020, a convenience sample of 49 herds was enrolled in this study. Blood sampling (16 to 29 cows per herd) was performed during the week before and during the 2 wk following calving to quantify the concentration of nonesterified fatty acids (NEFA) and β-hydroxybutyrate acids (BHBA), respectively...

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In multiple instance learning (MIL), a bag represents a sample that has a set of instances, each of which is described by a vector of explanatory variables, but the entire bag only has one label/response. Though many methods for MIL have been developed to date, few have paid attention to interpretability of models and results. The proposed Bayesian regression model stands on two levels of hierarchy, which transparently show how explanatory variables explain and instances contribute to bag responses. Moreover, two selection problems are simultaneously addressed; the instance selection to find out the instances in each bag responsible for the bag response, and the variable selection to search for the important covariates...

The association between the exposure of organochlorine pesticides (OCPs) and serum uric acid (UA) levels remained uncertain. In this study, to investigate the combined effects of OCP mixtures on hyperuricemia, we analyzed serum OCPs and UA levels in adults from the National Health and Nutrition Examination Survey (2005-2016). Four statistical models including weighted logistic regression, weighted quantile sum (WQS), quantile g-computation (QGC), and bayesian kernel machine regression (BKMR) were used to assess the relationship between mixed chemical exposures and hyperuricemia...

BACKGROUND: To describe the past, present and future burden of pancreatitis in older adults, and to explore cross-national inequalities across socio-demographic index (SDI). METHODS: Data on pancreatitis in older adults, including mortality and disability-adjusted life years (DALYs) rates, were collected from the Global Burden of Disease (GBD) 2019 study. Temporal trends were measured using joinpoint analyses and predicted using a Bayesian age-period-cohort model...

Language models based on artificial neural networks increasingly capture key aspects of how humans process sentences. Most notably, model-based surprisals predict event-related potentials such as N400 amplitudes during parsing. Assuming that these models represent realistic estimates of human linguistic experience, their success in modeling language processing raises the possibility that the human processing system relies on no other principles than the general architecture of language models and on sufficient linguistic input...

We present a fully Bayesian autoencoder model that treats both local latent variables and global decoder parameters in a Bayesian fashion. This approach allows for flexible priors and posterior approximations while keeping the inference costs low. To achieve this, we introduce an amortized MCMC approach by utilizing an implicit stochastic network to learn sampling from the posterior over local latent variables. Furthermore, we extend the model by incorporating a Sparse Gaussian Process prior over the latent space, allowing for a fully Bayesian treatment of inducing points and kernel hyperparameters and leading to improved scalability...

BACKGROUND: Although both air pollution and aging are related to the development of liver cirrhosis, the role of biological aging in association of the mixture of fine particulate matter (PM2.5 ) and its constituents with liver cirrhosis was unknown. METHODS: This case-control retrospective study included 100 liver cirrhosis patients and 100 control subjects matched by age and sex. The concentrations of PM2.5 and its constituents were estimated for patients using machine-learning methods...

BACKGROUND: The effects of bempedoic acid in the secondary prevention setting have not been examined. METHODS: We used data from the overall and primary prevention reports of CLEAR - Outcomes to reconstruct data for the secondary prevention population. A Bayesian analyses was employed to calculate the posterior probability of benefit or harm for the outcomes of all-cause mortality, cardiovascular mortality, and major adverse cardiovascular events (MACE). Relative effect sizes are presented as risk ratios (RR) with 95% credible intervals (CrI), which represent the intervals that true effect sizes are expected to fall in with 95% probability, given the priors and model...

PURPOSE: To compare the efficacy, safety, and tolerability of cenobamate with other newer anti-seizure medications (ASMs) including brivaracetam, eslicarbazepine, lacosamide, perampanel, and zonisamide, approved for adjunctive treatment of drug-resistant focal-onset seizures (FOS) in adults with epilepsy. METHODS: A systematic literature review (SLR) was conducted to obtain relevant efficacy, safety, and tolerability data for ASMs for the treatment of drug-resistant FOS...

BACKGROUND: Blurred work-non-work boundaries can have negative effects on mental health, including sleep. OBJECTIVES: In a randomised control trial, we aimed to assess the effectiveness of an online recovery training programme designed to improve symptoms of insomnia in a working population exposed to blurred boundaries. METHODS: 128 participants with severe insomnia symptoms (Insomnia Severity Index ≥15) and working under blurred work and non-work conditions (segmentation supplies <2...

BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals from the same joint remains challenging due to their similar brain spatial distribution. NEW METHOD: We designed experiments involving three motor imagery tasks-wrist extension, wrist flexion, and wrist abduction-with six participants...

Lake ecological processes and nutrient patterns are increasingly affected by water level variation around the world. Still, the long-term effects of water level change on lake ecosystems and their implications for suitable lake level management have rarely been studied. Here, we studied the ecosystem dynamics of a mesotrophic lake located in the cold and arid region of northern China based on long-term paleo-diatom and fishery records. Utilizing a novel Copula-Bayesian Network model, possible hydrological-driven ecosystem evolution was discussed...

Prescribed opioids are a mainstay pain treatment after traumatic injury, but a subgroup of patients may be at risk for continued opioid use. We evaluated the predictive utility of a traditional screening tool, the Opioid Risk Tool (ORT), and two other measures: average in-hospital milligram morphine equivalents (MME) per day and an assessment of opioid demand in predicting pain outcomes. Assessments of pain-related outcomes (pain intensity, interference, injury-related stress, and need for additional pain treatment) were administered at 2 weeks and 12 months post-discharge in a sample of 34 patients hospitalized for traumatic injury...

BACKGROUND: The growth and development of organism were dependent on the effect of genetic, environment, and their interaction. In recent decades, lots of candidate additive genetic markers and genes had been detected by using genome-widely association study (GWAS). However, restricted to computing power and practical tool, the interactive effect of markers and genes were not revealed clearly. And utilization of these interactive markers is difficult in the breeding and prediction, such as genome selection (GS)...

Monitoring methane emissions is crucial in mitigating climate change as it has a relatively short atmospheric lifetime of about 12 years and a significant radiative forcing impact. To measure the impact of methane-controlling policies and techniques, a deep understanding of methane emissions is of great importance. Remote sensing offers scalable approaches for monitoring methane emissions at various scales, from point-source high-resolution monitoring to regional and global estimates. The TROPOMI satellite instrument provides daily XCH4 data globally, offering the opportunity to monitor methane at a moderate spatial resolution with an acceptable level of sensitivity...

BACKGROUND: Distributed lag non-linear models (DLNMs) are the reference framework for modelling lagged non-linear associations. They are usually used in large-scale multi-location studies. Attempts to study these associations in small areas either did not include the lagged non-linear effects, did not allow for geographically-varying risks or downscaled risks from larger spatial units through socioeconomic and physical meta-predictors when the estimation of the risks was not feasible due to low statistical power...