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PubMedDate not supplied

Open-loop-feedback control of serum drug concentrations: pharmacokinetic approaches to drug therapy.

Recent developments to optimize open-loop-feedback control of drug dosage regimens, generally applicable to pharmacokinetically oriented therapy with many drugs, involve computation of patient-individualized strategies for obtaining desired serum drug concentrations. Analyses of past therapy are performed by least squares, extended least squares, and maximum a posteriori probability Bayesian methods of fitting pharmacokinetic models to serum level data. Future possibilities for truly optimal open-loop-feedback therapy with full Bayesian methods, and conceivably for optimal closed-loop therapy in such data-poor clinical situations, are also discussed. Implementation of these various therapeutic strategies, using automated, locally controlled infusion devices, has also been achieved in prototype form.

Aged↗

PubMed2026

Exploring hormonal influences on nicotine craving and use across the perinatal period: A prospective longitudinal study.

INTRODUCTION: Perinatal nicotine use is common despite well-documented adverse consequences. We examined associations between reproductive-related hormones with nicotine craving and use during the perinatal period to identify potential novel intervention points. METHODS: All participants reported use of nicotine during the perinatal period. Participants were enrolled at gestational week ≥ 36 and followed to postpartum week 12 via daily surveys (i.e., nicotine craving via 100-point scale, dichotomous use) and weekly hormone measurement in saliva (cortisol, oxytocin) or dried blood spots (progesterone, estradiol, testosterone, dehydroepiandrosterone sulfate). Bayesian mixed-effects models accounted for within-person correlation while estimating hormone effects. RESULTS: Participants (n = 46) were 28.9 ± 4.9 years old. During follow-up, exclusive combustible cigarettes (n = 20), electronic nicotine delivery systems (ENDS; n = 13), or dual (n = 2) use was observed, with variability in use and craving across participants and over time. During pregnancy, higher oxytocin was linked to greater craving (β=16.31, 95% CI: 3.71, 28.83). Greater peripartum declines in oxytocin were associated with more craving (β=8.71, 95% CI: 0.75, 16.93) and use (β=1.13, 95% CI: 0.05, 2.43). During postpartum, lower estradiol was linked to more craving (β=-1.17, 95% CI: -2.15, -0.18) and use (β=-0.40, 95% CI: -0.76, -0.03). In models simultaneously evaluating all postpartum hormones, the lone meaningful association was between estradiol and craving (β=-1.66, 95% CI: -2.84, -0.48). CONCLUSIONS: The results of this study suggest that oxytocin and estradiol may contribute to the risk of perinatal nicotine use. Additional research is needed to replicate our observations in more diverse study samples and explore implications for clinical intervention.

Bayesian↗

PubMed1993

Evaluating the quality of a probabilistic diagnostic system using different inferencing strategies.

In this paper we describe the evaluation of a probabilistic diagnostic system for patients with renal mass. Three inference models: Multi-membership Bayesian (MB), Minimal Diagnosis (MD) and Bayesian Network (BN), and 72 patients are used to illustrate three interrelated measures of system performance: accuracy, reliability and discriminating power. The inferencing strategies we tested demonstrated the kind of trade-offs in the performance measures that can be expected from imperfect systems. Ultimately, the purpose and expected use of a system should dictate the relative importance ascribed to different aspects of system performance.

Adolescent↗

PubMed2025

Coupling of spectroscopy and nitrogen-oxygen isotopes unveils the mechanisms of dissolved organic matter and nitrate pollution in lakes within the agro-pastoral transition zone.

Lakes in arid and semi-arid regions are subjected to severe ecological stress, such as organic pollution, eutrophication, and salinization, due to climate change and human activities. This study investigates Chagannur Lake, a typical arid-region lake that is representative and ecologically sensitive in Northern China's agro-pastoral ecotone, to uncover its pollution characteristics and mechanisms. We employed fluorescence spectroscopy and stable isotope analysis to trace dissolved organic matter (DOM) and nitrate sources. The DOM composition was dominated by microbial metabolic byproducts and protein-like substances, suggesting that microbial processes are key to organic matter transformation. Source apportionment revealed that pollutants primarily originated from livestock and poultry manure (37.6 %), agricultural fertilizers (35.6 %), and soil erosion (24.7 %), with agricultural fertilizers contributing most significantly in the Gogstai River (63.3 %). A structural equation model (SEM) coupling spectral and mass spectrometric data revealed that microbial transformation significantly impairs the lake's self-purification capacity, thereby promoting pollutant accumulation (path coefficient = 0.91,*p < 0.05). Moreover, microbial processes link endogenous and exogenous pollution, a mechanism effectively traced by isotopic and fluorescence indices (path coefficient = 0.55, ⁎⁎p < 0.01). These findings enhance the understanding of pollution sources and transformation mechanisms in arid-region lakes and offer foundational theoretical support for policymakers engaged in pollution control strategies.

Lakes↗

PubMed1995

Bayesian forecasting of serum vancomycin concentrations in neonates and infants.

A dynamic pharmacokinetic model for i.v. vancomycin administration was developed and tested in 47 neonates and infants. Twenty-nine patients (Group 1), having two or more concentrations, were used to estimate population parameters by nonlinear least-squares analysis. Multiple stepwise linear regression techniques showed that estimated creatinine clearance, Clcr, and postnatal age were significant demographic factors related to vancomycin clearance (CL). No strong associations were found for the apparent volume of distribution. A one-compartment model was constructed using the associations of CLcr and postnatal age with vancomycin CL. Eighteen patients (Group 2), receiving 35 courses of vancomycin therapy, with both initial and subsequent sets of peak and trough concentrations, were used to test the predictive performance of the model with and without the use of Bayesian forecasting. Using only population-based parameters, the respective mean error (ME) (bias) and mean absolute error (MAE) (precision) for predicting subsequent peak concentrations were -1.20 and 3.89 mg/L and for trough concentrations, 0.83 and 2.23 mg/L, respectively. For the Bayesian method, these values were, respectively, 0.45 and 4.13 mg/L for peak concentrations and 1.55 and 2.40 mg/L for trough concentrations. When predicted concentrations occurred within 30 days of feedback concentrations, the Bayesian method tended to be slightly less biased and more precise than the population-based parameters. The opposite was true > 30 days of the initial set of feedback concentrations. The use of population-specific pharmacokinetic parameters and Bayesian forecasting should allow accurate dosage regimen design as well as minimize the need for monitoring serum vancomycin concentrations in neonates and young infants.

Bayes Theorem↗

PubMed1991

Identifying the fertile phase of the human menstrual cycle.

The identification of the human fertile phase as the time during which a woman or a couple may conceive is elusive. The fertile time depends on many factors in each individual menstrual cycle and may be said to be more of a statistical than a physiological entity. This paper reviews the application of statistical methods to three areas related to conception and the fertile phase. The first is the prediction and detection of ovulation from serial measurements, such as hormones, basal body temperature and cervical mucus, throughout the menstrual cycle. Typically, such variables increase from some baseline level to a peak around ovulation (the most fertile time), then subside to low levels in the postovulatory phase. The statistical challenge is to detect the rise (signalling the onset of potential fertility) and subsequent fall. Analytic methods considered include thresholds, Bayesian change-point models and particularly the cumulative sum (cusum) technique which is both simple to apply and understand, and effective. The second area comprises appropriate methods of analysing and interpreting data from clinical studies of the fertile phase, especially in so-called natural family planning (NFP) where it is usual for women to observe several indices of potential fertility. Such studies usually try to establish the temporal relationships between markers of the fertile phase and examine the success of different combinations of markers in delineating the fertile time in comparison with a standard 'defined' phase, for example, the interval from three days before to two days after the peak of luteinizing hormone. The third area is the assessment of the probability of conception on certain days of the cycle, which is vital to the understanding of the fertile phase and its application to NFP. Direct estimation of such probabilities is impractical; instead, resort must be made to estimation by maximum likelihood of the parameters of specially constructed models. Suitable models are described. Finally, the need for a new prospective study of the probability of conception in relation to the markers of the fertile phase used in the symptothermal method of NFP is discussed.

Female↗

PubMed1995

Pharmacokinetics and pharmacodynamics of 21-day continuous oral etoposide in pediatric patients with solid tumors.

PURPOSE: The objectives of this study were to determine etoposide pharmacokinetics during continuous low-dose oral administration to children with solid tumors and to evaluate the relationships between parameters of etoposide systemic exposure and toxicity. PATIENTS AND METHODS: In this phase I study, children were administered oral etoposide (25 to 75 mg/m2/day) for 21 days as a diluted solution of the intravenous preparation, divided into three equal daily doses. Plasma pharmacokinetics were studied on day 1 of therapy in 18 children and again on day 21 in 14 of these children. Etoposide plasma concentration-time data were fitted to a first-order absorption, two-compartment model with use of bayesian estimation. Pharmacokinetic parameter estimates from day 1 were used to estimate steady-state etoposide systemic exposure in all children. Stepwise multivariate regression was used in an exploratory manner to determine patient, laboratory, or pharmacokinetic predictors of toxicity. RESULTS: Although there was substantial intrapatient variability, there was no difference in the area under the concentration-time curve [AUC(0-8hr)] measured at day 21 compared with the steady-state AUC(0-8hr) estimated from day 1 pharmacokinetic parameters (p = 0.64). Degree of neutropenia was best predicted by the estimated duration that steady-state plasma etoposide concentrations were maintained above 1 microgram/ml (t > 1 microgram/ml) rather than peak plasma concentrations, AUC(0-8hr), dosage, or other patient characteristics. Assuming a bioavailability of the oral solution of approximately 50%, the median etoposide systemic clearance was 21.4 ml/min/m2, a value similar to clearance estimates after intravenous etoposide in pediatric populations. CONCLUSION: We conclude that a parameter reflective of etoposide systemic exposure (t > 1 microgram/ml) correlates more strongly with neutropenia than does dosage or other patient characteristics.

Administration, Oral↗

PubMed1990

Modelling human tibia structural vibrations.

Mode shapes and natural frequencies of human long bones play an important role in the interpretation, prediction and control of their dynamic response to external mechanical loads. This paper describes an experimental and theoretical study of free vibrations in an excised human tibia. Experimentally, seven tibial natural frequencies in the range 0-3 kHz were identified through measured structural transfer functions. Theoretically, a beam type Finite Element model of a human tibia is suggested. Unknown parameters in this model are determined by a Bayesian parameter estimation approach, by which very fine model/observation-accordance was achieved with realistic parameter estimates. A sensitivity analysis of the model confirms that the human tibia in a vibrational sense is more uniform than its complicated geometry would immediately suggest. Accordingly, two simple tibia models are identified, based on uniform beam theory with inclusion of shear deformations.

Biomechanical Phenomena↗

PubMed2025

Leveraging functional annotations to map rare variants associated with Alzheimer disease with gruyere.

Increased availability of whole-genome sequencing (WGS) has facilitated the study of rare variants (RVs) in complex diseases. Multiple RV association tests are available to study the relationship between genotype and phenotype, but most do not fully leverage the availability of variant-level functional annotations. We propose genome-wide rare variant enrichment evaluation (gruyere), an empirical Bayesian framework that complements existing methods by learning global, trait-specific weights for functional annotations to improve variant prioritization. We apply gruyere to WGS data from the Alzheimer's Disease Sequencing Project to identify Alzheimer disease (AD)-associated genes and annotations. Growing evidence suggests that the disruption of microglial regulation is a key contributor to AD risk, yet existing methods have not examined rare non-coding effects that incorporate such cell-type-specific information. To address this gap, we (1) define per-gene non-coding RV test sets using predicted enhancer and promoter regions in microglia and other brain cell types (oligodendrocytes, astrocytes, and neurons) and (2) include cell-type-specific variant effect predictions (VEPs) as functional annotations. gruyere identifies 13 significant genetic associations not detected by other RV methods, four of which remain significant in omnibus tests. We find that deep-learning-based VEPs for splicing, transcription factor binding, and chromatin state are highly predictive of functional non-coding RVs. Our study establishes a robust framework incorporating functional annotations, coding RVs, and cell-type-associated non-coding RVs to perform genome-wide association tests, uncovering AD-relevant genes and annotations.

Alzheimer Disease↗

PubMed2026

Comparative effects of pharmacological interventions in the prophylactic treatment of tension-type headache: systematic review and network meta-analysis.

BACKGROUND: Tension-type headache (TTH) is the most common neurological disorder. The comparative effect of pharmacological interventions for TTH prophylaxis remains unclear. We aimed to assess the comparative effects of pharmacological interventions in the prophylactic treatment of TTH. METHODS: Ovid Medline, Embase, and Cochrane were searched from inception to 12 December, 2025. Randomized controlled trials (RCTs) of medications compared to placebo or another medication for preventing TTH were included. The primary outcome was headache days per month. A Bayesian random-effect model was employed as the primary analysis of chronic TTH. RESULTS: Thirty-five RCTs were included, 33 (88.6%) RCTs involved chronic TTH patients, and 24 RCTs provided available data for meta-analysis. Amitriptyline 100 mg presented more reduction of monthly headache days than placebo at 4 and 8 weeks (4 weeks: MD -6.59, 95% CrI -11.22 to -0.64; 8 weeks: MD -6.14, 95% CrI -10.27 to -0.87). BTX-A 100 U can reduce monthly headache days (MD -3.79, 95% CrI -7.16 to -0.33). Amitriptyline 100 mg was the highest-ranked treatment for monthly headache days at 4 (SUCRA 0.85), 8 (SUCRA 0.85), and 24 (SUCRA 0.87) weeks; 12 weeks was lidocaine 25 ml (SUCRA 0.75). Amitriptyline 100 mg and BTX-A 500 U showed a higher adverse event rate than placebo. CONCLUSION: Amitriptyline 100 mg and BTX-A 100 U may be options to reduce monthly headache days in patients with chronic TTH. Given the low to very low certainty of evidence, high risk of bias, and high heterogeneity, more studies are needed. TRIAL REGISTRATION: PROSPERO (CRD42025639586).

Humans↗

PubMed2026

Bayesian inference of lineage trees by joint analysis of single-cell multimodal lineage-tracing data with BiLinT.

The advent of single-cell lineage-tracing technologies has enabled the simultaneous profiling of gene expression and lineage barcodes. However, accurate, high-resolution reconstruction of cell lineage trees remains challenging because most existing approaches treat these modalities separately and therefore fail to fully exploit their complementary information. Here we present BiLinT, a Bayesian framework that jointly models multimodal single-cell lineage-tracing data for lineage tree reconstruction. BiLinT integrates barcode evolution (a continuous-time Markov chain) with gene expression dynamics (an Ornstein-Uhlenbeck process) within a unified probabilistic model. Across synthetic and real data sets, BiLinT provides accurate lineage-tree reconstruction and reveals differentiation-associated clonal structure and developmental fate biases.

Journal Article↗

PubMed2022

Comparison on Major Gene Mutations Related to Rifampicin and Isoniazid Resistance between Beijing and Non-Beijing Strains of Mycobacterium tuberculosis: A Systematic Review and Bayesian Meta-Analysis.

Objective: The Beijing strain of Mycobacterium tuberculosis (MTB) is controversially presented as the predominant genotype and is more drug resistant to rifampicin and isoniazid compared to the non-Beijing strain. We aimed to compare the major gene mutations related to rifampicin and isoniazid drug resistance between Beijing and non-Beijing genotypes, and to extract the best evidence using the evidence-based methods for improving the service of TB control programs based on genetics of MTB. Method: Literature was searched in Google Scholar, PubMed and CNKI Database. Data analysis was conducted in R software. The conventional and Bayesian random-effects models were employed for meta-analysis, combining the examinations of publication bias and sensitivity. Results: Of the 8785 strains in the pooled studies, 5225 were identified as Beijing strains and 3560 as non-Beijing strains. The maximum and minimum strain sizes were 876 and 55, respectively. The mutations prevalence of rpoB, katG, inhA and oxyR-ahpC in Beijing strains was 52.40% (2738/5225), 57.88% (2781/4805), 12.75% (454/3562) and 6.26% (108/1724), respectively, and that in non-Beijing strains was 26.12% (930/3560), 28.65% (834/2911), 10.67% (157/1472) and 7.21% (33/458), separately. The pooled posterior value of OR for the mutations of rpoB was 2.72 ((95% confidence interval (CI): 1.90, 3.94) times higher in Beijing than in non-Beijing strains. That value for katG was 3.22 (95% CI: 2.12, 4.90) times. The estimate for inhA was 1.41 (95% CI: 0.97, 2.08) times higher in the non-Beijing than in Beijing strains. That for oxyR-ahpC was 1.46 (95% CI: 0.87, 2.48) times. The principal patterns of the variants for the mutations of the four genes were rpoB S531L, katG S315T, inhA-15C > T and oxyR-ahpC intergenic region. Conclusion: The mutations in rpoB and katG genes in Beijing are significantly more common than that in non-Beijing strains of MTB. We do not have sufficient evidence to support that the prevalence of mutations of inhA and oxyR-ahpC is higher in non-Beijing than in Beijing strains, which provides a reference basis for clinical medication selection.

Isoniazid↗

PubMed1994

Mixed Bayesian networks: a mixture of Gaussian distributions.

Mixed Bayesian networks are probabilistic models associated with a graphical representation, where the graph is directed and the random variables are discrete or continuous. We propose a comprehensive method for estimating the density functions of continuous variables, using a graph structure and a set of samples. The principle of the method is to learn the shape of densities from a sample of continuous variables. The densities are approximated by a mixture of Gaussian distributions. The estimation algorithm is a stochastic version of the Expectation Maximization algorithm (Stochastic EM algorithm). The inference algorithm corresponding to our model is a variant of junction three method, adapted to our specific case. The approach is illustrated by a simulated example from the domain of pharmacokinetics. Tests show that the true distributions seem sufficiently fitted for practical application.

Algorithms↗

PubMed1987

A Bayesian approach to the multiplicity problem for significance testing with binomial data.

Statistical analyses of simple tumor rates from an animal experiment with one control and one treated group typically consist of hypothesis testing of many 2 X 2 tables, one for each tumor type or site. The multiplicity of significance tests may cause excessive overall false-positive rates. This paper presents a Bayesian approach to the problem of multiple significance testing. We develop a normal logistic model that accommodates the incidences of all tumor types or sites observed in the current experiment simultaneously as well as their historical control incidences. Exchangeable normal priors are assumed for certain linear terms in the model. Posterior means, standard deviations, and Bayesian P-values are computed for an average treatment effect as well as for the effects on individual tumor types or sites. Model assumptions are checked using probability plots and the sensitivity of the parameter estimates to alternative priors is studied. The method is illustrated using tumor data from a chronic animal experiment.

Analysis of Variance↗

PubMed1994

Designing an optimal experiment for Bayesian estimation: application to the kinetics of iodine thyroid uptake.

We consider the problem of designing an optimal experiment for Bayesian estimation of the parameters of a non-linear model. When their distribution is known, the Bayesian approach allows individual estimation from a small number of measurements; the design determines the accuracy of the estimates. We propose to optimize this design by maximizing a general criterion: the expectation of the information supplied by the experiment. This approach is applied to optimize the two sampling times for Bayesian estimation of the kinetics of radioiodine thyroid uptake from an estimated non-parametric prior distribution.

Bayes Theorem↗

PubMedDate not supplied

Piperacillin-tazobactam pharmacokinetics in patients with intraabdominal infections.

STUDY OBJECTIVE: To determine the appropriate compartmental and noncompartmental pharmacokinetic parameters for intravenous piperacillin and tazobactam. DESIGN: Sequential selection of patients entered into a randomized, open-label clinical efficacy trial. SETTING: Los Angeles County-University of Southern California Medical Center. PARTICIPANTS: Sequential sample of 18 patients admitted for intraabdominal infections and consented into a comparative antibiotic trial. INTERVENTIONS: Patients received piperacillin 4 g plus tazobactam 500 mg by intravenous intermittent infusion every 8 hours. MEASUREMENTS AND MAIN RESULTS: The estimated noncompartmental pharmacokinetic parameters (mean +/- SD) for piperacillin and tazobactam, respectively, were as follows: maximum concentration in plasma 218.7 +/- 48.9 micrograms/ml and 27.8 +/- 9.1 micrograms/ml; half-life 1.07 +/- 0.22 hours and 1.00 +/- 0.27 hours; elimination rate constant 0.67 +/- 0.13 hr-1 and 0.73 +/- 0.18 hr-1; area under the concentration-time curve from zero hour to infinity 288.5 +/- 71.25 mg.hr/L and 36.3 +/- 9.55 mg.hr/L; total plasma clearance 14.75 +/- 3.93 L/hour and 14.78 +/- 4.39 L/hour; renal clearance 5.69 +/- 1.94 L/hour and 7.85 +/- 3.37 L/hour; volume of distribution at steady state 21.00 +/- 4.18 L and 22.47 +/- 8.27 L; and mean residence time 1.72 +/- 0.29 hours and 1.79 +/- 0.35 hours. CONCLUSION: Our findings were similar to those in other surgical patient models. The two-compartmental model best described piperacillin and tazobactam disposition in our patients. Bayesian analyses of the two-compartment models of piperacillin and tazobactam were able to predict trough, peak, and 2-hour postadministration levels without bias.

Abdomen↗

PubMed1978

Assessment of the EMIT-(TM) technique as a screening test for opiates and methadone for a methadone maintenance clinic and its calibration by Bayesian statistics.

1. The performance of the semi-quantitative enzyme multiplied immunoassay technique (EMIT, Syva Corp.) for opiates and methadone has been examined as a screening procedure of urine samples from a methadone maintenance programme. The predictive value model that is based upon Bayesian statistics was used to determine screening levels for the EMIT assays. 2. With a predictive value of a negative result of 100%, the EMIT opiate assay can be used to show the absence of the indicated drugs, while positive results can be confirmed by a non-immunological technique. A screening level of 1.0 micrograms/ml for the opiate assay, conforms to this model. 3. The EMIT methadone assay was shown to have a predictive value of a negative result of 28% with respect to thin-layer chromatographic (TLC) results. This discrepancy between EMIT and TLC can not be explained by sensitivity alone. The manufacturer's recommended 0.5 micrograms/ml cutoff has been used therefore for the methadone assay.

Chromatography, Thin Layer↗

PubMed1986

The formation of maintenance of delusions: a Bayesian analysis.

This paper argues that recent research on normal-belief formation is relevant to our understanding of the establishment and maintenance of delusions. Bayesian theory provides a normative model of the way in which evidence relevant to normal beliefs may be evaluated: this makes it possible to classify delusional beliefs in terms of deviations from optimal Bayesian inference. Some hypothetical forms of deviation appear to correspond closely to cognitive processes observed in some groups of deluded patients. Theories of the precise nature of the abnormal judgemental processes also have implications for psychological approaches to treatment of deluded patients. The role of hallucinations in the formation and/or maintenance of delusions and the extent to which the distortions of cognitive processes associated with delusions are content-specific or mood-specific are also considered.

Cognition Disorders↗