Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring.

We consider a novel class of semiparametric joint models for multivariate longitudinal and survival data with dependent censoring. In these models, unknown-fashion cumulative baseline hazard functions are fitted by a novel class of penalized-splines (P-splines) with linear constraints. The dependence between the failure time of interest and censoring time is accommodated by a normal transformation model, where both nonparametric marginal survival function and censoring function are transformed to standard normal random variables with bivariate normal joint distribution. Based on a hybrid algorithm together with the Metropolis-Hastings algorithm within the Gibbs sampler, we propose a feasible Bayesian method to simultaneously estimate unknown parameters of interest, and to fit baseline survival and censoring functions. Intensive simulation studies are conducted to assess the performance of the proposed method. The use of the proposed method is also illustrated in the analysis of a data set from the International Breast Cancer Study Group.

Release of the additive metals from 3 commonly used plastics during the degradation under the treatment of UV irradiation.

Additive metals are continuously released into the environment during the photo-degradation of plastics into microplastics, but this phenomenon has not been reported by many studies. Herein, we investigated the surface morphology changes along with the release of additive metals (Cr, Mn, Fe, Co, Cu, Zn, and Pb) during the degradation of three types of plastics, i.e., polypropylene (PP), polyethylene terephthalate (PET) and polyvinyl chloride (PVC), under UV light irradiation. FTIR results showed that 168 days of UV-irradiation led to the primary degradation of each plastic sample. The metal release could be found after 70 days UV-irradiation. The rate of metal release for the three plastics showed the following order: PP > PET ≈ PVC. In addition, the distribution and concentrations of the metals in the plastic could influence the release characteristics of each metal. Low release rate of Fe symbolized by the total metal release in the range of 4.28 ~10.27% as evident from the results of the primary degradation experiment, indicated the release of Fe occurring in the late stage of the plastic degradation or even in the microplastics-formation stage. As for the release of Co from PP, it was far lower than that of the other elements (0.35%), showing the same release characteristics as that of Fe. On the contrary, the release ratio of Pb from PP was 78.89% and was mainly concentrated in the early stage of the plastic degradation. The results help understanding the release behavior of the additive metals during the degradation of typical plastics under ultraviolet light irradiation.

Room temperature monitoring of SF6decomposition byproduct SO2F2based on TiO2/NiSO4composite nanofibers.

Sulfuryl fluoride (SO2F2) is one of the ideal decomposition components of sulfur hexafluoride (SF6), which is widely used as an insulating and arc extinguishing medium in gas-insulated switchgear. To detect the decomposition component of SF6at room temperature, the use of SO2F2is still a challenge. In this work, we have successfully fabricated TiO2nanofibers and nickel sulfate (NiSO4NPs) via simple electrospun and hydrothermal methods, followed by calcination process to improve the sensing performance. Metal oxide semiconductor materials (MOSs) are widely used in gas sensing applications due to their superior performance and fast recovery speed. Although the performance of our TiO2/NiSO4composite nanofiber sensor decreases at higher temperatures, it shows an excellent response to target gasses at room temperature. Ni-decoration on the outer surface of the nanofibers could maximize the sensing response of 100 ppm SO2F2by up to 189% at room temperature, showing that the TiO2/NiSO4composite nanofibers are 2.5 times superior to the pure TiO2nanofiber sensors. Thus, the approach for this novel composite nanofiber-based material is promising for the fabrication of superior gas sensors for decomposition of SF6.

Survival of Patients with Primary Cardiac Tumors in an 11-Year Single Center Study.

BACKGROUND: Primary cardiac tumors are rare, but few studies have examined the relationship between risk factors and the prognosis. The aim of this study was to provide a survival analysis and risk factors for mortality in patients with primary cardiac tumors. METHODS: We retrospectively enrolled 71 patients diagnosed with primary cardiac tumors from June 2006 to November 2017 in our hospital. Patients' population characteristics, treatment information, pathology, and follow-up data were obtained and analyzed. RESULTS: Of the 71 patients, 60 cases were benign, and 11 cases were malignant. Sex, age, New York Heart Association classification, the percentage of peripheral embolism, and surgery had no significant difference between benign and malignant groups (P >.05), but the percentage of arrhythmia, leg edema, and mortality rate was higher in the malignant tumor group than in the benign tumor group (P <.05). Compared with the benign tumor group, the percentage of biatrial lesions in the malignant tumor group was significantly higher (P <.05). Moreover, Independent risk factors included the treatment choice, pathology type, and number of tumor lesions (P <.05). CONCLUSION: Our study suggests that conservative therapy, malignant cardiac tumor, and biatrial tumor lesion are independent risk factors for poor prognosis.

Influence analysis for skew-normal semiparametric joint models of multivariate longitudinal and multivariate survival data.

The normality assumption of measurement error is a widely used distribution in joint models of longitudinal and survival data, but it may lead to unreasonable or even misleading results when longitudinal data reveal skewness feature. This paper proposes a new joint model for multivariate longitudinal and multivariate survival data by incorporating a nonparametric function into the trajectory function and hazard function and assuming that measurement errors in longitudinal measurement models follow a skew-normal distribution. A Monte Carlo Expectation-Maximization (EM) algorithm together with the penalized-splines technique and the Metropolis-Hastings algorithm within the Gibbs sampler is developed to estimate parameters and nonparametric functions in the considered joint models. Case deletion diagnostic measures are proposed to identify the potential influential observations, and an extended local influence method is presented to assess local influence of minor perturbations. Simulation studies and a real example from a clinical trial are presented to illustrate the proposed methodologies. Copyright © 2017 John Wiley & Sons, Ltd.

Bayesian variable selection and estimation in semiparametric joint models of multivariate longitudinal and survival data.

This paper presents a novel semiparametric joint model for multivariate longitudinal and survival data (SJMLS) by relaxing the normality assumption of the longitudinal outcomes, leaving the baseline hazard functions unspecified and allowing the history of the longitudinal response having an effect on the risk of dropout. Using Bayesian penalized splines to approximate the unspecified baseline hazard function and combining the Gibbs sampler and the Metropolis-Hastings algorithm, we propose a Bayesian Lasso (BLasso) method to simultaneously estimate unknown parameters and select important covariates in SJMLS. Simulation studies are conducted to investigate the finite sample performance of the proposed techniques. An example from the International Breast Cancer Study Group (IBCSG) is used to illustrate the proposed methodologies.

Confidence intervals construction for difference of two means with incomplete correlated data.

BACKGROUND: Incomplete data often arise in various clinical trials such as crossover trials, equivalence trials, and pre and post-test comparative studies. Various methods have been developed to construct confidence interval (CI) of risk difference or risk ratio for incomplete paired binary data. But, there is little works done on incomplete continuous correlated data. To this end, this manuscript aims to develop several approaches to construct CI of the difference of two means for incomplete continuous correlated data. METHODS: Large sample method, hybrid method, simple Bootstrap-resampling method based on the maximum likelihood estimates (B 1) and Ekbohm's unbiased estimator (B 2), and percentile Bootstrap-resampling method based on the maximum likelihood estimates (B 3) and Ekbohm's unbiased estimator (B 4) are presented to construct CI of the difference of two means for incomplete continuous correlated data. Simulation studies are conducted to evaluate the performance of the proposed CIs in terms of empirical coverage probability, expected interval width, and mesial and distal non-coverage probabilities. RESULTS: Empirical results show that the Bootstrap-resampling-based CIs B 1, B 2, B 4 behave satisfactorily for small to moderate sample sizes in the sense that their coverage probabilities could be well controlled around the pre-specified nominal confidence level and the ratio of their mesial non-coverage probabilities to the non-coverage probabilities could be well controlled in the interval [0.4, 0.6]. CONCLUSIONS: If one would like a CI with the shortest interval width, the Bootstrap-resampling-based CIs B 1 is the optimal choice.

Confidence interval construction for the difference between two correlated proportions with missing observations.

Under the assumption of missing at random, eight confidence intervals (CIs) for the difference between two correlated proportions in the presence of incomplete paired binary data are constructed on the basis of the likelihood ratio statistic, the score statistic, the Wald-type statistic, the hybrid method incorporated with the Wilson score and Agresti-Coull (AC) intervals, and the Bootstrap-resampling method. Extensive simulation studies are conducted to evaluate the performance of the presented CIs in terms of coverage probability and expected interval width. Our empirical results evidence that the Wilson-score-based hybrid CI and the Wald-type CI together with the constrained maximum likelihood estimates perform well for small-to-moderate sample sizes in the sense that (i) their empirical coverage probabilities are quite close to the prespecified confidence level, (ii) their expected interval widths are shorter, and (iii) their ratios of the mesial non-coverage to non-coverage probabilities lie in interval [0.4, 0.6]. An example from a neurological study is used to illustrate the proposed methodologies.

[Effect of Electroacupunctrue on ERp57 in NAFLD Rats].

OBJECTIVE: To investigate the effect of electroacupunctrue on ERp57 in non-alcoholic fatty liver disease (NAFLD) rats, and study the therapeutic mechanism of electroacupunctrue in patients with NAFLD. METHODS: Sixty male SD rats were randomly divided into common diet group (n = 15) and high-fat diet group (n = 45). 5 weeks later, two rats from the two groups were executed and confirmed that the model was successful. Then 10 rats in common diet group were chosen as control group (Control), and 40 rats in high-fat diet group were randomly chosen and divided into diet group 1 (D1), diet group 2 (D2), electroacupuncture group 1 (EA) and electroacupuncture group 2 (EA2) (n = 10 each). D1 and EA1 were fed by high fat diet; D2 and EA2 were fed with common diet. In EA1 and EA2, filiform needle acupuncture was applied to ST36, SP6 and Liv3 and electroacupunctrue was applied to one-side of ST36, SP6 for 20 min once daily for 4 weeks. The rats in each group were weighed per-week. After the treatment the changes of blood lipid and liver functions of these rats were observed. ERp57 gene expression and protein expression were detected by RT-PCR and Western blot, and expression of ERp57 downstream SREBP-1c was detected. RESULTS: The body mass of D1 increased slowly and were lower than D2 and EA1 (P < 0.05); the body weights of EA2 increased rapidly and were higher than EA1 (P < 0.05), but without significant difference with D2 (P > 0.05). The contents of blood lipid, liver functions and the expression of ERp57 and SREBP-1c were significantly higher than those in Control, D2 and EA1 (P < 0.05). While compared to D2 and EA1 respectively, the index mentioned above in EA2 decreased more significantly (P < 0.05). CONCLUSION: Electroacupunctrue can decrease expression of ERp57 to improve endoplasmic reticulum stress (ERS) of rats with NAFLD and then decrease expression of SREBP-1c to regulate rat lipid, which could be one of mechanism to cure NAFLD.

Semiparametric Bayesian inference on skew-normal joint modeling of multivariate longitudinal and survival data.

We propose a semiparametric multivariate skew-normal joint model for multivariate longitudinal and multivariate survival data. One main feature of the posited model is that we relax the commonly used normality assumption for random effects and within-subject error by using a centered Dirichlet process prior to specify the random effects distribution and using a multivariate skew-normal distribution to specify the within-subject error distribution and model trajectory functions of longitudinal responses semiparametrically. A Bayesian approach is proposed to simultaneously obtain Bayesian estimates of unknown parameters, random effects and nonparametric functions by combining the Gibbs sampler and the Metropolis-Hastings algorithm. Particularly, a Bayesian local influence approach is developed to assess the effect of minor perturbations to within-subject measurement error and random effects. Several simulation studies and an example are presented to illustrate the proposed methodologies.

Synthesis, molecular docking and biological evaluation of 3-arylfuran-2(5H)-ones as anti-gastric ulcer agent.

3-Arylfuran-2(5H)-one derivatives show good antibacterial activity and were determined as tyrosyl-tRNA synthetase (TyrRS) inhibitors. In a systematic medicinal chemistry exploration, we demonstrated chemical opportunities to treat infections caused by Helicobacter pylori. Twenty 3-arylfuran-2(5H)-ones were synthesized and evaluated for anti-H. pylori, antioxidant and anti-urease activities which are closely interconnected with H. pylori infection. The results displayed that some of the compounds show excellent antioxidant activity, and good anti-H. pylori and urease inhibitory activities. Out of these compounds, 3-(3-methylphenyl)furan-2(5H)-one (b9) showed the most potent antioxidant activity (IC50=8.2 µM) and good anti-H. pylori activity (MIC50=2.6 µg/mL), and it can be used as a good candidate for discovering novel anti-gastric ulcer agent.

Testing non-inferiority of a new treatment in three-arm clinical trials with binary endpoints.

BACKGROUND: A two-arm non-inferiority trial without a placebo is usually adopted to demonstrate that an experimental treatment is not worse than a reference treatment by a small pre-specified non-inferiority margin due to ethical concerns. Selection of the non-inferiority margin and establishment of assay sensitivity are two major issues in the design, analysis and interpretation for two-arm non-inferiority trials. Alternatively, a three-arm non-inferiority clinical trial including a placebo is usually conducted to assess the assay sensitivity and internal validity of a trial. Recently, some large-sample approaches have been developed to assess the non-inferiority of a new treatment based on the three-arm trial design. However, these methods behave badly with small sample sizes in the three arms. This manuscript aims to develop some reliable small-sample methods to test three-arm non-inferiority. METHODS: Saddlepoint approximation, exact and approximate unconditional, and bootstrap-resampling methods are developed to calculate p-values of the Wald-type, score and likelihood ratio tests. Simulation studies are conducted to evaluate their performance in terms of type I error rate and power. RESULTS: Our empirical results show that the saddlepoint approximation method generally behaves better than the asymptotic method based on the Wald-type test statistic. For small sample sizes, approximate unconditional and bootstrap-resampling methods based on the score test statistic perform better in the sense that their corresponding type I error rates are generally closer to the prespecified nominal level than those of other test procedures. CONCLUSIONS: Both approximate unconditional and bootstrap-resampling test procedures based on the score test statistic are generally recommended for three-arm non-inferiority trials with binary outcomes.

Confidence-interval construction for rate ratio in matched-pair studies with incomplete data.

Matched-pair design is often used in clinical trials to increase the efficiency of establishing equivalence between two treatments with binary outcomes. In this article, we consider such a design based on rate ratio in the presence of incomplete data. The rate ratio is one of the most frequently used indices in comparing efficiency of two treatments in clinical trials. In this article, we propose 10 confidence-interval estimators for the rate ratio in incomplete matched-pair designs. A hybrid method that recovers variance estimates required for the rate ratio from the confidence limits for single proportions is proposed. It is noteworthy that confidence intervals based on this hybrid method have closed-form solution. The performance of the proposed confidence intervals is evaluated with respect to their exact coverage probability, expected confidence interval width, and distal and mesial noncoverage probability. The results show that the hybrid Agresti-Coull confidence interval based on Fieller's theorem performs satisfactorily for small to moderate sample sizes. Two real examples from clinical trials are used to illustrate the proposed confidence intervals.

Implantable cardiac monitor and leadless pacemaker in the management of syncope due to intermittent high-degree atrioventricular block: a case report.

BACKGROUND: Lead dislodgements, tricuspid valve failure, and wound infections are prominent issues addressed by leadless pacemakers (LPM). These devises have emerged as viable alternatives to conventional transvenous pacemakers. LPMs offer minimized complications and effective pacing, particularly beneficial for elderly patients with a low body mass index (BMI) who are at heightened infection of risk. The Micra AV leadless pacemaker was released in the US in 2020, featuring a VDD pacing mode akin to conventional pacemakers. It senses atrial activity to pace ventricular beats while maintaining the natural atrioventricular activation sequence. Micra AV achieves atrioventricular synchronization through mechanical sensing principles. Ongoing research aims to assess its efficacy, implantation feasibility, and clinical safety. CASE PRESENTATION: An 83-year-old man with a history of syncope was the focus of this case study. An implantable cardiac monitor (ICM) recorded occasional high-degree atrioventricular block in the patient. Subsequently, the Micra AV was implanted via the left femoral vein, and its settings were adjusted in accordance with data obtained from the ICM. No significant issues regarding pacing threshold or impedance were found during the follow-up examinations post-surgery. Importantly, the patient experienced a noticeable reduction in symptoms compared to before the implantation. DISCUSSION: This case underscores the significance of ICM monitoring in elucidating cardiac events leading to syncope and guiding appropriate treatment. It also highlights the successful outcomes and reliable implantation of the Micra AV for managing high-degree atrioventricular block. This study contributes to the growing body of evidence supporting the adoption of leadless pacemakers as a viable option for patients requiring cardiac pacing, particularly those vulnerable to complications associated with traditional pacemakers. It provides real-world evidence of Micra AV's efficacy and safety, further validating its role in clinical practice.

Study on the photoaging process and metal ion release of plastic films with two kinds of structures in marine environment: Aliphatic and aromatic polymers.

The prevalence of plastics in the oceans has significantly intensified microplastic pollution, contributing to broader marine secondary pollution issues. This paper examines how plastic structure affects the aging characteristics of plastics and the release of metal ions, to better understand this secondary source of marine pollution. This study simulate the photoaging of plastics in natural environments, focusing on aliphatic and aromatic polymers. The results showed that the photodegradation degree was higher for aliphatic than aromatic polymers. All polymers contained thirteen detectable metals, with their release increasing over time due to photoaging, The release dynamics of these metal ions correlated more strongly with the level of polymer degradation rather than with the polymer structure itself, adhering to a second-order kinetic model driven by surface and intraparticle diffusion processes. The results will help control and treat marine plastic pollution.

Homogeneity test of difference between two correlated proportions in stratified matched-pair studies.

Stratified matched-pair studies are often designed for adjusting stratification factors in modern medical researches. This article investigates a homogeneity test of differences between two correlated proportions in stratified matched-pair studies. We propose three test procedures, including an asymptotic test, bootstrap test, and multiple comparison procedures, and determine sample size requirements for such tests in a stratified matched-pair study. Simulation studies are conducted to evaluate the performance of the three test procedures and the accuracy of our derived sample size formulas. Empirical results show that (1) the likelihood ratio statistic is robust, while the score statistic and the modified score statistic are conservative in some cases of our considered settings; (2) the likelihood ratio statistic and the score statistic with the bootstrap method and the MaxT procedure behave satisfactorily in the sense that their type I error rates are close to the pre-given significance level; and (3) the derived sample size formulas are rather accurate. A real example from a clinical laboratory study is used to illustrate the proposed methodologies.

Simultaneous confidence intervals of risk differences in stratified paired designs.

In stratified matched-pair studies, risk difference between two proportions is one of the most frequently used indices in comparing efficiency between two treatments or diagnostic tests. This article presents five simultaneous confidence intervals and two bootstrap simultaneous confidence intervals for risk differences in stratified matched-pair designs. The proposed confidence intervals are evaluated with respect to their coverage probabilities, expected widths, and ratios of the mesial noncoverage to noncoverage probability. Empirical results show that (1) hybrid simultaneous confidence intervals outperform nonhybrid simultaneous confidence intervals; (2) hybrid simultaneous confidence intervals based on median estimator outperform those based on maximum likelihood estimator; and (3) hybrid simultaneous confidence intervals incorporated with Wilson score and Agresti coull intervals and the bootstrap t-percentile simultaneous interval based on median unbiased estimators behave satisfactorily for small to large sample sizes in the sense that their empirical coverage probabilities are close to the prespecified nominal confidence level, and their ratios of the mesial noncoverage to noncoverage probabilities lie in [0.4,0.6] and are hence recommended. Real examples from clinical studies are used to illustrate the proposed methodologies.

Beneficial effects of upgrading to His-Purkinje system pacing in patients with pacing-induced cardiomyopathy: a systematic review and meta-analysis.

Background: The purpose of this study was to evaluate the effectiveness of His-Purkinje system pacing (HPSP) in the management of patients with pace-induced cardiomyopathy (PICM). Methods: PubMed, Embase, Web of Science, and the Cochrane Library were searched comprehensively to collect related studies published from the inception of databases to June 1, 2022. R 4.04 software, including the Metafor package, matrix package, and the Meta package, was utilized to conduct the singe-arm meta-analysis. The methodology index for non-randomized studies (MINORS) was used to assess the methodological quality of the included studies. Results: A total of seven studies were included, involving 164 PICM patients. The meta-analysis showed that HPSP ameliorated the left ventricular ejection fraction (LVEF) by 13.41% (95% CI [11.21-15.61]), improved the New York Heart Association (NYHA) classification by 1.02 (95% CI [-1.41 to -0.63]), and shortened the QRS duration (QRSd) by 60.85 ms (95% CI [-63.94 to -57.75]), resulting in improved cardiac functions in PICM patients. Besides, HPSP reversed the ventricular remodeling, with a 32.46 ml (95% CI [-53.18 to -11.75]) decrease in left ventricular end systolic volume (LVESV) and a 5.93 mm (95% CI [-7.68 to -4.19]) decrease in left ventricular end-diastolic dimension (LVEDD). HPSP also showed stable electrical parameters of pacemakers, with a 0.07 V (95% CI [0.01-0.13]) increase in pacing threshold, a 0.02 mV (95% CI [-0.85 to 0.90]) increase in sensed R-wave amplitude, and a 31.12 Ω reduction in impedance (95% CI [-69.62 to 7.39]). Compared with LBBP, HBP improved LVEF by 13.28% (95% CI [-11.64 to 14.92]) vs 14.43% (95% CI [-13.01 to 15.85]), ameliorated NHYA classification by 1.18 (95% CI [-1.97 to -0.39]) vs 0.95 (95% CI [-1.33 to -0.58]), shortened QRSd by 63.16 ms (95% CI [-67.00 to -59.32]) vs 57.98 ms (95% CI [-62.52 to -53.25]), and decreased LVEDD by 4.12 mm (95% CI [-5.79 to -2.45]) vs 6.26 mm (95% CI [-62.52 to -53.25]). The electrical parameters of the pacemaker were stable in both groups. Conclusions: This meta-analysis showed that HPSP could significantly improve cardiac function, promote reverse remodeling, and provide stable electrical parameters of pacemakers for PICM patients.

Test procedures for disease prevalence with partially validated data.

Investigating the prevalence of a disease is an important topic in medical studies. Such investigations are usually based on the classification results of a group of subjects according to whether they have the disease. To classify subjects, screening tests that are inexpensive and nonintrusive to the test subjects are frequently used to produce results in a timely manner. However, such screening tests may suffer from high levels of misclassification. Although it is often possible to design a gold-standard test or device that is not subject to misclassification, such devices are usually costly and time-consuming, and in some cases intrusive to the test subjects. As a compromise between these two approaches, it is possible to use data that are obtained by the method of double-sampling. In this article, we derive and investigate four test statistics for testing a hypothesis on disease prevalence with double-sampling data. The test statistics are implemented through both the asymptotic method suitable for large samples and approximate unconditional method suitable for small samples. Our simulation results show that the approximate unconditional method usually produces a more satisfactory empirical type I error rate and power than its asymptotic counterpart, especially for small to moderate sample sizes. The results also suggest that the score test and the Wald test based on an estimate of variance with parameters estimated under the null hypothesis outperform the others. An real example is used to illustrate the proposed methods.

Investigation on Depression of College Students Majoring in Physical Education and Nonphysical Education: A StudyBased on the Age Region and Gender of 374 Students.

In the research on the relationship between depression and college students' major, there are some differences in the degree of depression between sports major and nonsports major students. Based on these results, we assume that there is the possibility of emotional differences between professional and nonprofessional sports. A total of 374 samples of students majoring in physical education and nonphysical education at the same university were analyzed by using the methods of literature review and data analysis. A total of 188 subjects, including 121 males and 253 females (186 majoring in sports and nonsports), were asked to fill in the SDS (Self-Rating Depression Scale). SDS is widely used in rough screening, emotional state evaluation, investigation, and scientific research of outpatients in clinical psychology departments. The research obtained the difference in depression degree in the whole sample and further compared the depression degree of students of different ages and native places. Statistical analysis was performed on all data using SPSS 23.0 software. Basic data description, paired chi-square analysis, and covariance analysis were used. The results show that in this sample, the maximum value (minimum/maximum value) of one item of the total depression score of nonphysical education students exceeds the average value by 3 standard deviations, and this shows that the general level of depression scores of non-PE majors is high; most non-PE majors are in mild depression, which is equal to the number of PE majors who are in a normal mood; and nonsports majors in cities are more likely to have mild depression.