Highest Posterior Density Research Articles

A Bayesian reanalysis of the CULPRIT-SHOCK trial.

The optimal revascularization strategy for patients with acute myocardial infarction (AMI), cardiogenic shock (CS), and multivessel disease remains controversial. The CULPRIT-SHOCK trial compared culprit lesion-only vs. immediate multivessel percutaneous coronary intervention (PCI), providing important data but leaving efficacy questions unresolved. To address lingering uncertainties and gain deeper insights, we performed a Bayesian reanalysis of the CULPRIT-SHOCK trial data. We conducted a Bayesian re-analysis of the CULPRIT-SHOCK trial data using non-informative, sceptical, and enthusiastic priors. Relative risks (RRs) with 95% highest posterior density (HPD) intervals were calculated. We defined the minimal clinically important difference (MCID) as RR < 0.84. We performed subgroup analyses for key patient characteristics and assessed secondary outcomes and safety endpoints. Probabilities of benefit, achieving MCID, and harm were computed. Results are presented as median RR with probabilities of effect sizes. Bayesian reanalysis showed a median RR of 0.82 (95% HPD 0.66-1.04) with a non-informative prior, indicating a 95% probability of benefit and 59% probability of achieving MCID. Subgroup analyses revealed potentially stronger effects in males (RR 0.78, 73% probability of MCID), patients without diabetes (RR 0.76, 79% probability of MCID), and those with non-anterior ST-segment elevation MI (STEMI; RR 0.74, 76% probability of MCID). Secondary outcomes suggested potential benefits in mortality (RR 0.85) and need for renal replacement therapy (RR 0.72) but increased risks of recurrent MI (RR 2.84) and urgent revascularization (RR 2.88). Our Bayesian reanalysis provides intuitive insights by quantifying probabilities of treatment effect sizes, offering further evidence favouring the culprit lesion-only PCI strategy in AMI patients with CS and multivessel disease. The analysis demonstrates a high probability of overall benefit, with a notable chance of achieving a minimally clinically important difference, particularly in specific subgroups. These findings not only support the consideration of culprit lesion-only PCI in certain patient populations but also underscore the need for careful risk-benefit assessment. Furthermore, our hypothesis-generating subgroup analyses, which show varying probabilities of achieving MCID, illuminate promising avenues for future targeted investigations in this critical patient population.

Estimating the Confidence Intervals for the Coefficients of Variation Delta-Gamma Distributions

A common application of the coefficient of variation (CV), which is the ratio of the population standard deviation to the population mean, is frequently used to assess quality control and economic processes, among others. The fiducial quantity approach, Bayesian confidence intervals (CIs) using the Jeffreys, uniform, or normal-gamma-beta (NGB) priors, and highest posterior density (HPD) intervals using the Jeffreys, uniform, or NGB priors were used to provide estimators for the CI for the ratio of CV of two delta-gamma distributions. An evaluation of their performance in terms of average length and coverage probability was carried out using Monte Carlo simulations. The results of this study indicate that the HPD using the Jeffreys prior and fiducial quantity methods are the best for estimating the CI for the ratio of the CV of two delta-gamma distributions. Rainfall data from Mae Hong Son province in Thailand was used to illustrate their practicability when analyzing real-life processes.

A Molecular Temporal Evolutionary Framework of Land Plants and the Age of Angiosperms

A series of Bayesian molecular clock analyses with varying model combinations, parameters, and tree topologies were conducted to establish a temporal evolutionary framework of land plants and to estimate the age of angiosperms. The data consisted of five organellar and nuclear genes, 633 taxa, and 23 fossil calibration points (FCPs). The analyses were evaluated using an internal search thoroughness measure, effective sample sizes, and two external criteria: the consensus land plant phylogeny and a newly developed method that used the Hennigian reciprocal illumination principle to compare molecular age estimates of 21 nodes representing major land plant clades and the root split in green plants with those of their fossils in an a posteriori fashion. The results show that an analysis using a general time reversible (GTR) DNA substitution model, log normal branch-rate distribution, and Yule tree prior represented the best model combination, with the Birth-Death tree prior being equally optimal. This analysis estimated the age of the land plant crown group as 496.95 million years (MY), with a 95% highest posterior density (HPD) of 465.66–531.43 MY, and the age of the angiosperm crown group as 219.93 MY, with a 95% HPD of 184.09–256.82 MY. The former agrees with the fossil evidence, but the latter is significantly older than the fossil ages. A thorough examination of fossil evidence of angiosperms, as well as their evolutionary history in light of recent knowledge of morphology, physiology, and atmospheric CO2 concentration in the Mesozoic era, suggests that angiosperm radiation might have been delayed after their origin and that the current fossil record probably reflects only the products of that radiation, not the origin of angiosperms. Overall, the study shows that both molecular clock analyses and fossil studies, while agreeing on some aspects but disagreeing on others, can help develop a complete understanding of the temporal evolutionary history of land plants.

Classical and Bayesian inference of Cpc$\mathcal {C}_{pc}$ for Wilson–Hilferty distribution under progressively first‐failure type‐II censoring samples

AbstractThis study uses two frequentist approaches and the Bayesian method of estimation using progressively first‐failure type‐II censored data to estimate process capability index (PCI), , for the Wilson–Hilferty (WH) distribution. A competitive maximum product of spacing (MPS) method for estimation of is proposed in the frequentist method as an alternative to conventional likelihood (LK)‐based estimation. We have also taken into account the PS function in the Bayesian setup as an alternative to the conventional LK function, and both LK and PS‐based Bayesian estimates are given for . Further, the Bayes estimates are evaluated by applying Tierney–Kadane (TK) approximation method and Markov chain Monte Carlo (MCMC) method with the help of both LK and PS functions and Jeffrey's prior. Additionally, the approximate confidence intervals based on the suggested frequentist techniques as well as the Bayes highest posterior density (HPD) credible intervals are built for the index . In addition, two bootstrap confidence intervals are obtained. In the simulation exercise, the performance of the Bayes and traditional estimates of is assessed in terms of their mean squared errors, and the average width and coverage probabilities of the CIs and HPD intervals are compared. An actual data set from the electronic industries is reanalyzed in order to show the efficacy of the proposed index and estimation methodology.

Bayesian dynamic models to estimate the impact of halting vehicle fleets on the air quality: a case study from Medellín, Colombia

AbstractAccording to the World Health Organization (WHO, Ambient (outdoor) air pollution (who), 2020), outdoor air pollution is estimated to have caused 4.2 million premature deaths worldwide in 2019. Under this scenario, the development of statistical tools for assessing the impact of a possible reduction of fossil fuels-based transportation systems on air quality is more relevant than ever. This type of instruments can help policy makers to take the right path to tackle the problem of air pollution in urban environments. Thus, this work proposes a method to evaluate the impact of the reduction of vehicle fleets on air quality. The method is based on the construction of counterfactual time series, which represent observed air pollutants under a treatment of interest. In this case, the treatment of interest are the vehicle fleets on the streets. The construction of the counterfactual time series is based on Bayesian dynamic linear models. Several impact assessment measures are implemented, taking advantage of the counterfactual and observed time series (the observed pollutant without the treatment). The flexibility of the Bayesian approach allows easy inference of the impact quantities via high posterior density intervals. Some simulation analyses show that the method works well under different impact scenarios, and one application regarding Medellin’s case in Colombia is presented. For the application, it is shown that the drastic reduction in vehicle fleets during the COVID-19 mobility restrictions led to a significant reduction in the presence of different pollutants ($$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 , $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {NO}_{{x}}$$ NO x )

Bayesian analyses of multiple random change points in survival models with applications to clinical trials

ABSTRACT Single and multiple random change points (RCPs) in survival analysis have arisen naturally in oncology trials, where the time to hazard rate change differs from one subject to another. Recently, Xu formulated and discovered important properties of these survival models using a frequentist approach, allowing us to estimate the hazard rates, rate parameters of the exponential distributions for the RCPs, expected survival and hazard functions. However, these methods did not provide an estimation of the uncertainty or the confidence intervals for the parameters and their differences or ratios. Therefore, statistical inferences were not able to be drawn on the parameters and their comparisons. To solve this issue, this article implements a Gibbs sampler method to estimate the above parameters and the differences or ratios alongside the 100(1 − α )% highest posterior density (HPD) intervals calculated from Chen–Shao’s algorithm. The estimated rate parameters from the methods in Xu serve as empirical values in the Gibbs sampler method. Thus, formal statistical inferences can now be readily drawn. Simulation studies demonstrate that the proposed methods yield robust estimates, with the samples from the marginal posterior distributions converging rapidly and exhibiting favorable behavior. The 95% HPD intervals also demonstrate excellent coverage probabilities. This proposed method has a multitude of applications in clinical trials such as efficient clinical trial design and sample size adjustment based on the estimated parameter values at interim analyses.

Molecular cluster, transmission characteristics, origin and dynamics analysis of HIV-1 CRF59_01B in China: A molecular epidemiology study

PurposeThis study investigated for the HIV-1 CRF59_01B epidemic's spatiotemporal dynamics and its transmission networks in China. MethodsBetween 2007 and 2020, a total of 250 partial pol gene sequences of HIV-1 CRF59_01B were collected from four regions (10 Chinese provinces). Phylogenetic tree construction and cluster identification were then performed. The Bayesian skyline and birth–death susceptible–infected–removed models were employed for the phylodynamic analyses of subtypes and large clusters, respectively. Phylogenetic analyses and trait diffusion of these sequences were performed using Bayesian phylogenetic methods (beast-classic package). Distance-based molecular network analyses were performed to identify putative relationships. ResultsUsing a genetic distance threshold of 1.3 %, We identified 45 clusters that included 62.40 % (156/250) of the sequences. Three clusters (6.67 %, 3/45) had 10 or more sequences, and were considered "large clusters". Six clusters (13.33 %) included sequences from different regions (Southeast, Northeast, Southeast, and Central China). Thirteen clusters (28.89 %) included sequences of men who had sex with men only, three clusters (6.67 %) included sequences of heterosexuals only, and 12 clusters (26.67 %) included sequences of both groups. The substitution rate of CRF59_01B was 1.91 × 10–3 substitutions per site per year [95 % highest posterior density (HPD) interval: 1.39 × 10−3–2.49 × 10−3)], the time to the most recent common ancestor of CRF59_01B was to be 1992.83 (95 % HPD: 1977.97–2002.81). A Bayesian skyline plot revealed that the effective population size of CRF59_01B increased from 2000 to 2015 and remained stable after 2015. The large clusters showed continuous growth from 2013 to 2020. Phylogeographic analysis showed that CRF59_01B B most likely originated in Southeast China, with a posterior probability of 97.44 %, and then spread to other regions. ConclusionsOur study revealed the temporal and geographical origins of HIV-1 CRF59_01B as well as the process of transmission among various regions and risk groups in China, which can help develop targeted HIV prevention strategies.

Confidence Intervals for the Mean and Difference of Means of Birnbaum-Saunders Distributions with Application to Wind Speed Data

This paper proposes the confidence intervals for the mean and difference of means of Birnbaum-Saunders (BirSau) distributions based on the Bootstrap confidence interval (BCI), Percentile bootstrap confidence interval (PBCI), Generalized confidence interval (GCI), Bayesian credible interval (BayCrI) and the highest posterior density (HPD). The simulation study used R statistical software to evaluate the coverage probabilities and average lengths. The concerning results of the mean suggest that HPD is the recommended method for constructing confidence intervals in the BirSau distributions, except for small sample sizes where the GCI method proves more efficient. For the difference of means, PBCI emerges as the preferred way to construct confidence intervals, except in some cases where small sample sizes with the HPD method are more efficient. Moreover, the average lengths of these proposed confidence intervals decreased as both sample size and shape parameters increased. To illustrate the effectiveness of the suggested confidence intervals, we applied them to wind speed datasets collected in Ayutthaya and Ratchaburi provinces, Thailand.

The resurgence of influenza A/H3N2 virus in Australia after the relaxation of COVID-19 restrictions during the 2022 season.

This study retrospectively analyzed the genetic characteristics of influenza A H3N2 (A/H3N2) viruses circulating in New South Wales (NSW), the Australian state with the highest number of influenza cases in 2022, and explored the phylodynamics of A/H3N2 transmission within Australia during this period. Sequencing was performed on 217 archived specimens, and A/H3N2 evolution and spread within Australia were analyzed using phylogenetic and phylodynamic methods. Hemagglutinin genes of all analyzed NSW viruses belonged to subclade 3C.2a1b.2a.2 and clustered together with the 2022 vaccine strain. Complete genome analysis of NSW viruses revealed highly frequent interclade reassortments between subclades 3C.2a1b.2a.2 and 3C.2a1b.1a. The estimated earliest introduction time of the dominant subgroup 3C.2a1b.2a.2a.1 in Australia was February 22, 2022 (95% highest posterior density: December 19, 2021-March 13, 2022), following the easing of Australian travel restrictions, suggesting a possible international source. Phylogeographic analysis revealed that Victoria drove the transmission of A/H3N2 viruses across the country during this season, while NSW did not have a dominant role in viral dissemination to other regions. This study highlights the importance of continuous surveillance and genomic characterization of influenza viruses in the postpandemic era, which can inform public health decision-making and enable early detection of novel strains with pandemic potential.

Bayesian inference for reliability of K-out-of-N: G repairable retrial systems with mixed standbys, switching failure and reboot delay

Existing reliability studies on K-out-of-N: G repairable retrial systems with mixed standbys mainly consider the case where the standby switching is completely reliable and the repair time follows an exponential distribution, and most of them directly analyze the system reliability indices based on probability theory. Given the existence of such phenomenon as standby switching failure in engineering, this paper proposes a novel reliability model of K-out-of-N: G repairable retrial system with switching failure, and performs statistical inference on the reliability to realize the modeling and evaluation of the system. The considered system consists of mixed standbys and a repairer with vacation. When an operating component fails, the warm standby one is switched to the operating one immediately, and the probability of switching failure during the switchover process is p. In the case where the repair time of failed components follows a general distribution, based on the supplementary variable method and recursive algorithm, the steps for calculating the system steady-state availability are presented. In the case of unknown parameters for repair time and retrial time, the Bayesian estimator of the steady-state availability under the squared error loss function and highest posterior density (HPD) confidence interval are obtained. In numerical simulation, the system reliability inference is realized by using the Monte Carlo (MC) method, and the validity of the inference method is analyzed.

Inference on exponentiated Rayleigh distribution with constant stress partially accelerated life tests under progressive type-II censoring

This study aims to explore the issues of evaluating the parameters and the accelerating factor based on constant stress for partially accelerating life tests when the potential failure times have an exponentiated Rayleigh distribution. Within the framework of progressive Type-II censoring schemes, we employ the Newton-Raphson algorithm as an iterative methodology to gain the maximum likelihood estimates, accompanied by proof of the existence of these point estimators. We also construct asymptotic confidence intervals for interested parameters and acceleration factors by utilizing the asymptotical characteristics of the maximum likelihood estimators. The Bayesian estimations of unknown parameters are derived by using the independent gamma priors and dependent Gamma-Dirichlet prior on the basis of square error and relatively smooth LINEX loss functions, respectively. Furthermore, we adopt the importance sampling method to compute Bayesian point estimates and the credible intervals with the highest posterior density. To validate the effectiveness of the suggested approaches, a series of simulated experiments are carried out. Lastly, we conduct analyzes on two actual datasets to show the applicability of the suggested techniques.

Meta-Analysis of 5-Fraction Preoperative Radiotherapy for Soft Tissue Sarcoma.

Studies investigating preoperative 5-fraction radiation therapy (RT) for soft tissue sarcoma (STS) are limited. We performed a meta-analysis to determine the efficacy and safety of this treatment paradigm. This study-level meta-analysis was conducted using Bayesian methods. Statistical estimation for risk of outcome rates was conducted by posterior mean and 95% highest posterior density (HPD) intervals. Studies with 2-year local control (LC) and description of major wound complications (MWC) per the CAN-NCIC-SR2 study were included and served as the primary endpoints. Secondary endpoints included rates of acute and late toxicity. A total of 10 studies were identified and 7 met the inclusion criteria. Subgroup analyses were performed for ≥30 Gy vs <30 Gy. A total of 209 patients from 7 studies were included. Five studies used ≥30 Gy (n=144), and 2 studies <30 Gy (n=64). Median follow-up was 29 months (range: 21 to 57mo). Primary tumor location was lower extremity in 68% and upper extremity in 22%. Most tumors were intermediate or high grade (95%, 160/169), and 50% (79/158) were >10cm. The two-year LC for the entire cohort was 96.9%, and the rate of MWC was 30.6%. There was a trend toward improved LC with ≥ 30 Gy (95% HPD: 0.95 to 0.99 vs 0.84 to 0.99). There was no difference in MWC (95% HPD: 0.18 to 0.42 vs 0.17 to 0.55) or late toxicity between the groups. Preoperative 5-fraction RT for STS demonstrates excellent 2-year LC with MWC and toxicity similar to standard fractionation preoperative RT. Multi-institutional trials with a universal RT protocol are warranted.

Abstract PS16-01: Comparison of an Atezolizumab monotherapy window followed by Atezolizumab and chemotherapy vs. Atezolizumab and chemotherapy alone in triple negative breast cancer (TNBC) – final analysis of the neoadjuvant neoMono trial

Abstract Background: Improvement of systemic therapy of TNBC still is a medical need. Exploratory data from the neoadjuvant GeparNuevo trial suggested a benefit from an immune checkpoint inhibitor (ICI) monotherapy window in TNBC. The neoMono trial prospectively analyzed whether the addition of a preceding Atezolizumab monotherapy window prior to Atezolizumab and chemotherapy (CTX) improves pCR rates among patients (pts) with early TNBC. In an interim analysis after 100 pCR events, patients with unselected TNBC did not show a significant benefit from an Atezolizumab monotherapy window, while an exploratory analysis suggested a highly clinically relevant benefit among pts with PD-L1 positive TNBC. Here we present the final primary endpoint analysis. Methods: NeoMono is a phase 2 randomized multicenter trial that was planned to recruit a maximum of 458 female and male pts with primary TNBC (defined as ER/PR &amp;lt; 10% and HER2 negative) with tumor stages cT1c – cT4d (cN0 and cN+). As the protocol mandated termination of trial recruitment based on the results of the interim analysis, the final ITT population was limited to 359 pts. PD-L1 status had to be identifiable by central pathology by means of the VENTANA PD-L1 (SP142) assay and was defined by PD-L1 expression on immune cells (IC). Neoadjuvant treatment in both study arms consisted of Atezolizumab 1200 mg every 3 weeks in addition to neoadjuvant CTX (12 x Carboplatin/Paclitaxel q1w followed by 4x Epirubicin/Cyclophosphamide q3w). Combination therapy in arm A was preceded by an Atezolizumab monotherapy window of 840 mg once two weeks prior to initiation of combination therapy, while patients in arm B received no immune monotherapy window. Study goals are to compare the efficacy of neoadjuvant CTX + Atezolizumab with versus without a two-week atezolizumab monotherapy window preceding CTX + ICI (primary endpoint: pCR) and to identify biomarkers for response and resistance through analysis of sequential tissue and liquid biopsies. The neoMono statistical design uses Bayesian posterior probabilities (uniform prior distribution) and logistic regression to analyze the primary endpoint. Results: 180 pts in arm A and 179 in arm B from 34 study sites were included in the final primary endpoint analysis. Demographics and baseline characteristics as well as drug exposure were well-balanced in both arms. Posterior mean pCR rates in the ITT population in study arms A and B were 65.7% (95% high posterior density interval (HPDI): 58.5%, 72.5%) and 69% (62.2%, 75.9%), respectively. In an exploratory analysis stratified by PD-L1 IC status (negative: &amp;lt; 1% versus positive: ≥ 1%), pCR rates in arm A were 91.5% in the PD-L1 IC-positive group and 56.1% in the PD-L1 IC-negative group, the corresponding pCR rates in arm B were 82.2% and 64.5%, respectively. In a multivariate analysis of the ITT population including tumor size, nodal status, tumor grade, age and PD-L1 status, the odds ratio for achieving a pCR was 4.77 (p &amp;lt; 0.001) for PD-L1-positive and 2.36 (p=0.023) for grade 3 tumors. In an exploratory analysis including HER2 status, odds for achieving a pCR were significantly higher for patients with HER2-negative (IHC 0) vs. HER2-low tumors (OR 1.73, p=0.036). No new safety signals were observed. Conclusion: The final primary endpoint analysis of the neoMono trial demonstrated the highest pCR rates ever reported in a phase II/III trial in TNBC. While a significant impact of an ICI monotherapy window on the pCR rate after combination of CTX + ICI in an unselected ITT population could not be demonstrated, neoMono indicates for the first time in a randomized prospective setting that patients with immune active TNBC might derive particular benefit from a preceding ICI monotherapy window. The results of the neoMono trial are mainly justifying the conduction of a confirmative trial in immune active TNBC. However, our results underscore the potential role of pre-therapeutic ICI monotherapy window as part of future therapeutic concepts in TNBC. Citation Format: Hans-Christian Kolberg, Johannes Schumacher, Ramona Erber, Michael Braun, Peter A. Fasching, Eva-Maria Grischke, Christian Schem, Michael P. Lux, Mustafa Deryal, Oliver Hoffmann, Bernhard Heinrich, Georg Kunz, Kristina Lübbe, Petra Krabisch, Arndt Hartmann, Philip Raeth, Sabine Kasimir-Bauer, Cornelia Kolberg-Liedtke. Comparison of an Atezolizumab monotherapy window followed by Atezolizumab and chemotherapy vs. Atezolizumab and chemotherapy alone in triple negative breast cancer (TNBC) – final analysis of the neoadjuvant neoMono trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS16-01.

HIV-1 transmission dynamics among people who inject drugs on the US/Mexico border during the COVID-19 pandemic: a prospective cohort study

We examined HIV prevalence and transmission dynamics among people who inject drugs in the U.S./Mexico border region during the COVID-19 pandemic. People who inject drugs aged ≥18 years from 3 groups were recruited: people who inject drugs who live in San Diego (SD) and engaged in cross-border drug use in Tijuana, Mexico (SD CBDUs), and people who inject drugs in SD and Tijuana (TJ) who did not engage in cross-border drug use (NCBDUs). We computed HIV prevalence at baseline and bivariate incidence-density rates (IR) at 18-month follow-up. Bayesian phylogenetic analysis was used to identify local transmission clusters, estimate their age, and effective reproductive number (Re) over time within the clusters. At baseline (n=612), 26% of participants were female, 9% engaged in sex work, and HIVprevalencewas 8% (4% SD CBDU, 4% SD NCBDU, 16% TJ NCBDU). Nine HIV seroconversions occurred over 18 months, IR: 1.357 per 100 person-years (95% CI: 0.470, 2.243); 7 in TJ NCBDU and 2 in SD CBDU. Out of 16 identified phylogenetic clusters, 9 (56%) had sequences from both the U.S. and Mexico (mixed-country). The age of three youngest mixed-country dyads (2018-2021) overlapped with the COVID-related US-Mexico border closure in 2020. One large mixed-country cluster (N=15) continued to grow during the border closure (Re=4.8, 95% Highest Posterior Density (HPD) 1.5-9.1) with 47% engaging in sex work. Amidst the COVID-19 pandemic and the border closure, cross-border HIV clusters grew. Efforts to end the HIV epidemic in the U.S. should take into account cross-border HIV-1 transmission from Tijuana. Mobile harm reduction services and coordination with municipal HIV programs to initiate anti-retroviral therapy and pre-exposure prophylaxisis are needed to reduce transmission. This research was supported by the James B. Pendleton Charitable Trust and the San Diego Center for AIDS Research.

Emotional State Transitions in Trauma-Exposed Individuals With and Without Posttraumatic Stress Disorder

Posttraumatic stress disorder (PTSD) is marked by the contrasting symptoms of hyperemotional reactivity and emotional numbing (ie, reduced emotional reactivity). Comprehending the mechanism that governs the transition between neutral and negative emotional states is crucial for developing targeted therapeutic strategies. To explore whether individuals with PTSD experience a more pronounced shift between neutral and negative emotional states and how the intensity of emotional numbing symptoms impacts this shift. This cross-sectional study used hierarchical bayesian modeling to fit a 5-parameter logistic regression to analyze the valence ratings of images. The aim was to compare the curve's slope between groups and explore its association with the severity of emotional numbing symptoms. The study was conducted online, using 35 images with a valence range from highly negative to neutral. The rating of these images was used to assess the emotional responses of the participants. The study recruited trauma-exposed individuals (witnessed or experienced life-threatening incident, violent assault, or someone being killed) between January 17 and March 8, 2023. Participants completed the PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) (PCL-5). On the basis of DSM-5 criteria (endorsing at least 1 symptom from clusters B and C and 2 from D and E), participants were categorized as having probable PTSD (pPTSD) or as trauma-exposed controls (TECs). The main outcome was the slope parameter (b) of the logistic curve fitted to the valence rating. The slope parameter indicates the rate at which emotional response intensity changes with stimulus valence, reflecting how quickly the transition occurs between neutral and negatively valenced states. The secondary outcome was the association between emotional numbing (PCL-5 items 12-14) and the slope parameter. A total of 1440 trauma-exposed individuals were included. The pPTSD group (n = 445) was younger (mean [SD] age, 36.1 [10.9] years) compared with the TEC group (mean [SD] age, 41.5 [13.3] years; P < .001). Sex distribution (427 women in the TEC group vs 230 in the pPTSD group) did not significantly differ between groups (P = .67). The pPTSD group exhibited a steeper slope (mean slope difference, -0.255; 89% highest posterior density [HPD], -0.340 to -0.171) compared with the controls. Across all individuals (n = 1440), a robust association was found between the slope and emotional numbing severity (mean [SD] additive value, 0.100 [0.031]; 89% HPD, 0.051-0.15). Additional analysis controlling for age confirmed the association between emotional numbing and transition sharpness (mean [SD] additive value, 0.108 [0.032]; 89% HPD, 0.056-0.159), without evidence of an age-related association (mean [SD] additive value, 0.031 [0.033]; 89% HPD, -0.022 to 0.083). These findings support that individuals with PTSD undergo rapid transitions between neutral and negative emotional states, a phenomenon intensified by the severity of emotional numbing symptoms. Therapeutic interventions aimed at moderating these swift emotional transitions could potentially alleviate PTSD symptoms.

Genomic analysis reveals deep population divergence in the water snake Trimerodytes percarinatus (Serpentes, Natricidae).

Although several phylogeographic studies of Asian snakes have been conducted, most have focused on pitvipers, with non-venomous snakes, such as colubrids or natricids, remaining poorly studied. The Chinese keelback water snake (Trimerodytes percarinatus Boulenger) is a widespread, semiaquatic, non-venomous species occurring in China and southeastern Asia. Based on mitochondrial DNA (mtDNA) and single nucleotide polymorphism (SNP) data, we explored the population genetic structure, genetic diversity, and evolutionary history of this species. MtDNA-based phylogenetic analysis showed that T. percarinatus was composed of five highly supported and geographically structured lineages. SNP-based phylogenetic analysis, principal component analysis, and population structure analysis consistently revealed four distinct, geographically non-overlapping lineages, which was different from the mtDNA-based analysis in topology. Estimation of divergence dates and ancestral area of origin suggest that T. percarinatus originated ~12.68 million years ago (95% highest posterior density: 10.36-15.96 Mya) in a region covering southwestern China and Vietnam. Intraspecific divergence may have been triggered by the Qinghai-Xizang Plateau uplift. Population demographics and ecological niche modeling indicated that the effective population size fluctuated during 0.5 Mya and 0.002 Mya. Based on the data collected here, we also comment on the intraspecific taxonomy of T. percarinatus and question the validity of the subspecies T. p. suriki.

Statistical inference for Nadarajah-Haghighi distribution under unified hybrid censored competing risks data

Nadarajah and Haghighi distribution (NHD) inferences problem has been discussed under unified hybrid censoring scheme (UHCS) in the existence of competing risks model. Competing risks model is defined by time-to-failure under more than one cause of failure, which can be dependent or independent. This study focuses on discussing the case of failure partially observed causes of failure competing risks model. We obtain various inferences: we first obtain the MLE, in addition, we construct approximate confidence intervals (ACIs). Second, we obtain the Bayes estimator via SELF and related highest posterior density (HPD) using Markov Chain Monte Carlo (MCMC). Finally, an electrical appliances data set and simulation studies have been analyzed for further illustrations.

Estimation of the percentile of Birnbaum-Saunders distribution and its application to PM2.5 in Northern Thailand.

The Birnbaum-Saunders distribution plays a crucial role in statistical analysis, serving as a model for failure time distribution in engineering and the distribution of particulate matter 2.5 (PM2.5) in environmental sciences. When assessing the health risks linked to PM2.5, it is crucial to give significant weight to percentile values, particularly focusing on lower percentiles, as they offer a more precise depiction of exposure levels and potential health hazards for the population. Mean and variance metrics may not fully encapsulate the comprehensive spectrum of risks connected to PM2.5 exposure. Various approaches, including the generalized confidence interval (GCI) approach, the bootstrap approach, the Bayesian approach, and the highest posterior density (HPD) approach, were employed to establish confidence intervals for the percentile of the Birnbaum-Saunders distribution. To assess the performance of these intervals, Monte Carlo simulations were conducted, evaluating them based on coverage probability and average length. The results demonstrate that the GCI approach is a favorable choice for estimating percentile confidence intervals. In conclusion, this article presents the results of the simulation study and showcases the practical application of these findings in the field of environmental sciences.

Biogeographic history of Pterocarya (Juglandaceae) inferred from phylogenomic and fossil data

AbstractPterocarya (Juglandaceae) is disjunctly distributed in East Asia and the Caucasus region today, but its fossils are widely distributed in the Northern Hemisphere. We first inferred phylogeny with time estimation of Pterocarya under node‐dating (ND) based on plastomes of all eight extant species and tip‐dating (TD) based on plastomes and 69 morphological characters of 19 extant and extinct species, respectively. We compared the biogeographical reconstructions on the timetrees from ND and TD, respectively, and then compiled 83 fossil records and 599 current occurrences for predicting the potential distributions for the past and the future. The most recent comment ancestor of Pterocarya is inferred in East Asia at 40.46 Ma (95% highest posterior density [HPD]: 28.04–54.86) under TD and 26.81 Ma (95% HPD: 23.03–33.12) under ND. The current distribution was attributed to one dispersal and one vicariant event without fossils, but as many as six dispersal, six vicariant, and 11 local extinction events when considering fossils. Pterocarya migrated between East Asia and North America via the Bering Land Bridge during the early Oligocene and the early Miocene periods. With the closure of Turgai Strait, Pterocarya dispersed between East Asia and Europe through the Miocene. The potential distribution analyses indicated that Pterocarya preferred warm temperate regions across the Northern Hemisphere since the Oligocene, but the drastic temperature decline caused its extinction in high latitudes. Except for Pterocarya fraxinifolia and Pterocarya stenoptera, suitable habitats for this genus are predicted to contract by 2070 due to climate change.

Innovative use of sensor technology to study grazing behaviour and its associations with parasitic resistance in sheep

Gastrointestinal nematodes (GINs) are a concern for sheep production and are associated with significant economic losses globally, driving the need for effective management strategies. The aims of this research were first to determine the influence of GIN infections on sheep grazing behaviours, specifically grazing time (GT) and grazing event length (GL), and then to estimate the genetic and phenotypic correlation between faecal egg counts (FEC) and salivary specific IgA activity vs GT and GL. Data were collected from 146 Merino sheep on a commercial farm in Victoria, Australia. Faecal, saliva and body weight (BW) were collected at four time points (A: Oct 2019, B: early May 2020, C: late May 2020, and D: Jul 2020), while tri-axial accelerometer sensors recorded GT and GL for the length of 26 days between B and C. Univariate linear regression and Bayesian Generalised Linear Mixed Model, estimated using Markov Chain Monte Carlo, were used to assess the relationships between the behaviours and infection indicators. We found an increase in the logarithm of FEC was associated with a significant rise in grazing time (p < 0.05), suggesting compensatory behaviour in infected sheep. GT also accounted for 6% of the FEC variation. In contrast, the effect of IgA on GT was not significant (p > 0.05). There was a positive genetic and phenotypic correlation estimated between GT and FEC, however, the High Posterior Density interval for the genetic and phenotypic correlations between GT and FEC indicates some uncertainty in these estimates. These results imply that sheep may modify their grazing strategies as an adaptive response to parasitic infections to ease the impact on their nutritional intake. This study improves our understanding of how natural GIN infections affect sheep behaviour and highlights the potential to use animal behaviours as a precision livestock farming tool and in breeding for resilience against parasites.