A unified Minorization-Maximization approach for estimation of general mixture models

The mixed distribution model is often used to extract information from heteroge-neous data and perform modeling analysis.When the density function of mixed distribution is complicated or the variable dimension is high,it usually brings challenges to the parameter es-timation of the mixed distribution model.The application of MM algorithm can avoid complex expectation calculations,and can also solve the problem of high-dimensional optimization by decomposing the objective function.In this paper,MM algorithm is applied to the parameter estimation problem of mixed distribution model.The method of assembly and decomposition is used to construct the substitute function with separable parameters,which avoids the problems of complex expectation calculations and the inversion of high-dimensional matrices.

THE LONG TIME BEHAVIOR OF THE FRACTIONAL ORNSTEIN-UHLENBECK PROCESS WITH LINEAR SELF-REPELLING DRIFT

Let B^(H) be a fractional Brownian motion with Hurst index 1/2≤H<1.In this paper,we consider the equation(called the Ornstein-Uhlenbeck process with a linear self-repelling drift)dX_(t)^(H)=dB_(t)^(H)+σ X_(t)^(H)dt+vdt-θ(∫_(0)^(t)(X_(t)^(H)-X_(s)^(H))ds)dt,whereθ<0,σ,v∈ℝ.The process is an analogue of self-attracting diffusion(Cranston,Le Jan.Math Ann,1995,303:87–93).Our main aim is to study the large time behaviors of the process.We show that the solution X^(H)diverges to infinity as t tends to infinity,and obtain the speed at which the process X^(H)diverges to infinity.

BIG HANKEL OPERATORS ON HARDY SPACES OF STRONGLY PSEUDOCONVEX DOMAINS

In this article,we investigate the(big) Hankel operator H_(f) on the Hardy spaces of bounded strongly pseudoconvex domains Ω in C^(n).We observe that H_(f )is bounded on H~p(Ω)(1 <p <∞) if f belongs to BMO and we obtain some characterizations for Hf on H~2(Ω) of other pseudoconvex domains.In these arguments,Amar's L~p-estimations and Berndtsson's L^(2)-estimations for solutions of the ■_(b)-equation play a crucial role.In addition,we solve Gleason's problem for Hardy spaces H~p(Ω)(1 ≤p≤∞) of bounded strongly pseudoconvex domains.

Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Computational Analysis of Novel Extended Lindley Progressively Censored Data

A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing,bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is studied.In this research, using a progressive Type-II censored, various inferences of the MOL model parameters oflife are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of themodel parameters and various reliability measures are investigated. Against both symmetric and asymmetric lossfunctions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with theassumption of independent gamma priors. From the Fisher information data and the simulatedMarkovian chains,the approximate asymptotic interval and the highest posterior density interval, respectively, of each unknownparameter are calculated. Via an extensive simulated study, the usefulness of the various suggested strategies isassessedwith respect to some evaluationmetrics such as mean squared errors, mean relative absolute biases, averageconfidence lengths, and coverage percentages. Comparing the Bayesian estimations based on the asymmetric lossfunction to the traditional technique or the symmetric loss function-based Bayesian estimations, the analysisdemonstrates that asymmetric loss function-based Bayesian estimations are preferred. Finally, two data sets,representing vinyl chloride and repairable mechanical equipment items, have been investigated to support theapproaches proposed and show the superiority of the proposed model compared to the other fourteen lifetimemodels.

Recent trends in the epidemiology and clinical outcomes of inflammatory bowel disease in South Korea,2010-2018

BACKGROUND Inflammatory bowel disease(IBD)was previously regarded as a Western disease;however,its incidence is increasing in the East.The epidemiology of IBD in Asia differs significantly from the patterns in the West.AIM To comprehensively investigate the epidemiology of IBD in South Korea,inclu-ding its incidence,prevalence,medication trends,and outcomes.METHODS We analyzed claims data from the Health Insurance Review and Assessment Service and Rare and Intractable Diseases(RIDs),operated by the National Health Insurance Service of South Korea.Patients with IBD were identified based on the International Classification of Diseases,Tenth Revision,and RID diagnostic codes for Crohn’s disease(CD)and ulcerative colitis(UC)from 2010 to 2018.RESULTS In total,14498 and 31409 patients were newly diagnosed with CD and UC,respectively,between 2010 and 2018.The annual average incidence of CD was 3.11 cases per 105 person-years,and that of UC was 6.74 cases per 10^(5) person-years.Since 2014,the incidence rate of CD has been stable,while that of UC has steadily increased,shifting the peak age group from 50-year-olds in 2010 to 20-year-olds in 2018.The CD and UC prevalence increased consistently over the study period;the use of 5-aminosali-cylates and corticosteroids gradually decreased,while that of immunomodulators and biologics steadily increased in both CD and UC.The clinical outcomes of IBD,such as hospitalization and surgery,decreased during the study period.CONCLUSION The CD incidence has been stable since 2014,but that of UC has increased with a shift to a younger age at peak incidence between 2010 and 2018.IBD clinical outcomes improved over time,with increased use of immunomodu-lators and biologics.

Assessment of groundwater quantity, quality, and associated health risk of the Tano river basin, Ghana

In the Tano River Basin,groundwater serves as a crucial resource;however,its quantity and quality with regard to trace elements and microbiological loadings remain poorly understood due to the lack of groundwater logs and limited water research.This study presents a comprehensive analysis of the Tano River Basin,focusing on three key objectives.First,it investigated the aquifer hydraulic parameters and the results showed significant spatial variations in borehole depths,yields,transmissivity,hydraulic conductivity,and specific capacity.Deeper boreholes were concentrated in the northeastern and southeastern zones,while geological formations,particu-larly the Apollonian Formation,exhibit a strong influence on borehole yields.The study identified areas with high transmissivity and hydraulic conductivity in the southern and eastern regions,suggesting good groundwater avail-ability and suitability for sustainable water supply.Sec-ondly,the research investigated the groundwater quality and observed that the majority of borehole samples fall within WHO(Guidelines for Drinking-water Quality,Environmental Health Criteria,Geneva,2011,2017.http://www.who.int)limit.However,some samples have pH levels below the standards,although the groundwater generally qualifies as freshwater.The study further explores hydrochemical facies and health risk assessment,highlighting the dominance of Ca–HCO3 water type.Trace element analysis reveals minimal health risks from most elements,with chromium(Cr)as the primary contributor to chronic health risk.Overall,this study has provided a key insights into the Tano River Basin’s hydrogeology and associated health risks.The outcome of this research has contributed to the broader understanding of hydrogeologi-cal dynamics and the importance of managing groundwater resources sustainably in complex geological environments.

Post-fire recovery of Puya raimondii, vegetation and birds in the puna of Huascarán National Park, Perú

A large fire of 233 ha in Huascarán National Park in Peru provided an opportunity to compare plant and bird responses in burned and nearby unburned zones of the puna. Heights and live diameters of flagship Puya raimondii rosettes(assigned to four broad developmental phases), plant communities(66 species in 24 families and nine growth forms) and bird communities(77 species in six trophic guilds) were monitored after the fire. Although no mortality was observed, Puya raimondii plants were affected by the fire, losing approximately 60% of their photosynthetic area across all developmental phases, but recovered quickly during the first two years after fire. The comparison of Puya rosette recovery after fire was complicated by the changes in live rosette diameter for unburned plants, which showed plasticity of photosynthetic area linked to seasonal and annual fluctuations in precipitation in this relatively dry environment(decreased by 26% for mature adult plants over the study period). Fire caused an immediate change in the density, biomass and composition of vegetation. Although the species present remained similar, their abundances changed significantly immediately after the fire, with notable reductions in dominant tussock grasses. This provided opportunities for other plants, resulting in higher postfire diversity of plant species, genera, families and growth forms. In turn, the changes in vegetation after fire affected the composition of birds according to their trophic guild. Granivores largely disappeared,generalists were mostly unaffected, and other guilds showed a more complex response. As the vegetation recovered, most displaced birds returned within approximately one year.

Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT Scan: From Concepts toward Clinical Explainability

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT scans.This study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 diagnosis.This paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT scan.Firstly,an efficient U-shaped transformer network is integrated for lung image segmentation.Then,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input image.Secondly,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer Network.Experimental evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical significance.The Conformer Network achieves 97.40% of detection accuracy under cross-validation settings.Our model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our model.The findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

Einstein Hybrid Structure of q-Rung Orthopair Fuzzy Soft Set and Its Application for Diagnosis of Waterborne Infectious Disease

This research is devoted to diagnosing water-borne infectious diseases caused by floods employing a novel diagnosis approach,the Einstein hybrid structure of q-rung orthopair fuzzy soft set.This approach integrates parts of fuzzy logic and soft set theory to develop a robust alternative for disease detection in stressful situations,especially in areas affected by floods.Compared to the traditional intuitionistic fuzzy soft set and Pythagorean fuzzy soft set,the q-rung orthopair fuzzy soft set(q-ROFSS)adequately incorporates unclear and indeterminate facts.The major objective of this investigation is to formulate the q-rung orthopair fuzzy soft Einstein hybrid weighted average(q-ROFSEHWA)operator and its specific characteristics.Moreover,our stated operator is implementing intelligentmulti-criteria group decision-making(MCGDM)methodology.Floods are severe natural catastrophes that raise the risk of diseases and epidemics,particularly those caused by contaminants in the water,such as gastrointestinal diseases,respiratory infections,vector-borne diseases,skin infections,and water-borne parasites.The designed MCGDM strategy tackles the prevalence of certain conditions in flood-affected patients.A comparative investigation determined that the suggested method for detecting water-borne infectious disease due to floods is more effective and productive than conventional methods because of its logical structure.

An Intelligent MCGDM Model in Green Suppliers Selection Using Interactional Aggregation Operators for Interval-Valued Pythagorean Fuzzy Soft Sets

Green supplier selection is an important debate in green supply chain management(GSCM),attracting global attention from scholars,especially companies and policymakers.Companies frequently search for new ideas and strategies to assist them in realizing sustainable development.Because of the speculative character of human opinions,supplier selection frequently includes unreliable data,and the interval-valued Pythagorean fuzzy soft set(IVPFSS)provides an exceptional capacity to cope with excessive fuzziness,inconsistency,and inexactness through the decision-making procedure.The main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers(IVPFSNs)and create two interaction operators-the intervalvalued Pythagorean fuzzy soft interaction weighted average(IVPFSIWA)and the interval-valued Pythagorean fuzzy soft interaction weighted geometric(IVPFSIWG)operators,and analyze their properties.These operators are highly advantageous in addressing uncertain problems by considering membership and non-membership values within intervals,providing a superior solution to other methods.Moreover,specialist judgments were calculated by the MCGDM technique,supporting the use of interaction AOs to regulate the interdependence and fundamental partiality of green supplier assessment aspects.Lastly,a statistical clarification of the planned method for green supplier selection is presented.

Improving the radiological diagnosis of hepatic artery thrombosis after liver transplantation: Current approaches and future challenges

Hepatic artery thrombosis(HAT)is a devastating vascular complication following liver transplantation,requiring prompt diagnosis and rapid revascularization treatment to prevent graft loss.At present,imaging modalities such as ultrasound,computed tomography,and magnetic resonance play crucial roles in diagnosing HAT.Although imaging techniques have improved sensitivity and specificity for HAT diagnosis,they have limitations that hinder the timely diagnosis of this complication.In this sense,the emergence of artificial intelligence(AI)presents a transformative opportunity to address these diagnostic limitations.The development of machine learning algorithms and deep neural networks has demonstrated the potential to enhance the precision diagnosis of liver transplant complications,enabling quicker and more accurate detection of HAT.This article examines the current landscape of imaging diagnostic techniques for HAT and explores the emerging role of AI in addressing future challenges in the diagnosis of HAT after liver transplant.

Nutritional epigenetics education improves diet and attitude of parents of children with autism or attention deficit/hyperactivity disorder

BACKGROUND Unhealthy maternal diet leads to heavy metal exposures from the consumption of ultra-processed foods that may impact gene behavior across generations,creating conditions for the neurodevelopmental disorders known as autism and attention deficit/hyperactivity disorder(ADHD).Children with these disorders have difficulty metabolizing and excreting heavy metals from their bloodstream,and the severity of their symptoms correlates with the heavy metal levels measured in their blood.Psychiatrists may play a key role in helping parents reduce their ultra-processed food and dietary heavy metal intake by providing access to effective nutritional epigenetics education.AIM To test the efficacy of nutritional epigenetics instruction in reducing parental ultra-processed food intake.METHODS The study utilized a semi-randomized test and control group pretest-posttest pilot study design with participants recruited from parents having a learning-disabled child with autism or ADHD.Twenty-two parents who met the inclusion criteria were randomly selected to serve in the test(n=11)or control(n=11)group.The test group participated in the six-week online nutritional epigenetics tutorial,while the control group did not.The efficacy of the nutritional epigenetics instruction was determined by measuring changes in parent diet and attitude using data derived from an online diet survey administered to the participants during the pre and post intervention periods.Diet intake scores were derived for both ultra-processed and whole/organic foods.Paired sample t-tests were conducted to determine any differences in mean diet scores within each group.RESULTS There was a significant difference in the diet scores of the test group between the pre-and post-intervention periods.The parents in the test group significantly reduced their intake of ultra-processed foods with a preintervention diet score of 70(mean=5.385,SD=2.534)and a post-intervention diet score of 113(mean=8.692,SD=1.750)and the paired t-test analysis showing a significance of P<0.001.The test group also significantly increased their consumption of whole and/or organic foods with a pre-intervention diet score of 100(mean=5.882,SD=2.472)and post-intervention diet score of 121(mean=7.118,SD=2.390)and the paired t-test analysis showing a significance of P<0.05.CONCLUSION Here we show nutritional epigenetics education can be used to reduce ultra-processed food intake and improve attitude among parents having learning-disabled children with autism or ADHD.

Determination of the time of refractive stability after uneventful phacoemulsification in Indian eyes

BACKGROUND Knowledge about refractive stabilization and the accuracy of postoperative refractive error measurements are crucial for improved patient outcomes after phacoemulsification.Existing guidelines typically recommend waiting 4-6 wk before prescribing corrective lenses.Our research focused on identifying factors that influence refractive errors in the early stages of post-cataract surgery,thus contributing to the existing literature on this topic.AIM To investigate the time required for refraction stability after uneventful phacoemulsification surgery.METHODS We compared the variation and statistical significance of the difference in spherical,cylindrical components,and the spherical equivalent between the 1-and 6-wk follow-up period in a group of 257 eyes that underwent uneventful phacoemulsification with foldable intraocular lens implantation,all performed by a single experienced surgeon.The Wilcoxon-Signed Rank Test was utilized to assess the magnitude of the change and determine its statistical significance.The refractive stability was defined as the point at which the change in spherical equivalent was within±0.5 dioptres for two consecutive visits.RESULTS The average age of the patients was 64.9±8.9 yr.The differences observed in both the visits in spherical power(0.1±0.2),cylinder power(0.3±0.4),and spherical equivalent(0.2±0.2)were minimal and not statistically significant.The majority of eyes(93.4%)achieved refractive stability within 6 wk after the surgery.The cylindrical power differed between age groups at the 6th wk post-operative and the difference was statistically significant(P value 0.013).There were no significant differences in refractive stability when considering sex and axial length.CONCLUSION Phacoemulsification with foldable intraocular lens implantation results in no significant changes in refraction for the majority of cases during the 6-wk follow-up period.Therefore,a spectacle prescription can be given at the completion of 1 wk.

Effect of Different Mulch Materials on Yield and Nutrition Profile of Common Capsicum (Capsicum annuum) Cultivars in Bangladesh

Capsicum is a nutritious vegetable and its cultivation in farms is getting popular in Bangladesh. Although many efforts have lain to explore better yielding and nutritionally rich cultivars with suitable modern cultivation techniques but still have to find the desired outcome. Thus, it’s necessary to conduct further research to identify the high-yielding and nutritious capsicum cultivars in Bangladesh. An experiment was conducted from July 2021 to June 2022 at the Bangladesh Institute of Research and Training on Applied Nutrition (BIRTAN) research field with three cultivars of capsicum: B0 = California Wonder, B1 = BARI Misti Morich-1 and B2 = BARI Misti Morich-2 and three mulching: T0 = No mulching, T1 = Water hyacinth, T2 = Poly Mulching in randomized complete block design with three replications to identify better quality capsicum cultivar and suitable mulching material. Among cultivars the BARI Misti Morich-2 (B2) showed increased agronomic parameters like number of branches and effective branches per plant, leaves length and width, consequently yield and yield contributing traits were also enhanced like fruits per plant, fruit length, fruit diameter and yield per plant (25.97%, 4.54%, 3.64% and 21.43%, respectively). Poly Mulching (T2) increased agronomic traits, yield traits and yield (0.61 kg) than BARI Misti Morich-1 (T1). The combined effect of B2T2 increased the number of branches per plant, effective branches per plant, leaves length and breadth by 40%, 90%, 15.57% and 26.22%, respectively, hence resulting in an increased yield of 20%. BARI Misti Morich-2 cultivar showed an increase in Fe, Zn and Vitamin-C content of 26.24% and 23.10%, 8.82% and 5.14%, and 6.03% and 5.74% than B0 and B1 cultivars, respectively. Therefore, BARI Misti Morich-2 exhibited the improved agronomic, yield and nutritional traits of capsicum under poly mulching among other cultivars in Bangladesh.

Exploring a New Lifetime Distribution for Modelling the Waiting Time of Bank Customers

The fitting of lifetime distribution in real-life data has been studied in various fields of research. With the theory of evolution still applicable, more complex data from real-world scenarios will continue to emerge. Despite this, many researchers have made commendable efforts to develop new lifetime distributions that can fit this complex data. In this paper, we utilized the KM-transformation technique to increase the flexibility of the power Lindley distribution, resulting in the Kavya-Manoharan Power Lindley (KMPL) distribution. We study the mathematical treatments of the KMPL distribution in detail and adapt the widely used method of maximum likelihood to estimate the unknown parameters of the KMPL distribution. We carry out a Monte Carlo simulation study to investigate the performance of the Maximum Likelihood Estimates (MLEs) of the parameters of the KMPL distribution. To demonstrate the effectiveness of the KMPL distribution for data fitting, we use a real dataset comprising the waiting time of 100 bank customers. We compare the KMPL distribution with other models that are extensions of the power Lindley distribution. Based on some statistical model selection criteria, the summary results of the analysis were in favor of the KMPL distribution. We further investigate the density fit and probability-probability (p-p) plots to validate the superiority of the KMPL distribution over the competing distributions for fitting the waiting time dataset.

Modelling the Survival of Western Honey Bee Apis mellifera and the African Stingless Bee Meliponula ferruginea Using Semiparametric Marginal Proportional Hazards Mixture Cure Model

Classical survival analysis assumes all subjects will experience the event of interest, but in some cases, a portion of the population may never encounter the event. These survival methods further assume independent survival times, which is not valid for honey bees, which live in nests. The study introduces a semi-parametric marginal proportional hazards mixture cure (PHMC) model with exchangeable correlation structure, using generalized estimating equations for survival data analysis. The model was tested on clustered right-censored bees survival data with a cured fraction, where two bee species were subjected to different entomopathogens to test the effect of the entomopathogens on the survival of the bee species. The Expectation-Solution algorithm is used to estimate the parameters. The study notes a weak positive association between cure statuses (ρ1=0.0007) and survival times for uncured bees (ρ2=0.0890), emphasizing their importance. The odds of being uncured for A. mellifera is higher than the odds for species M. ferruginea. The bee species, A. mellifera are more susceptible to entomopathogens icipe 7, icipe 20, and icipe 69. The Cox-Snell residuals show that the proposed semiparametric PH model generally fits the data well as compared to model that assume independent correlation structure. Thus, the semi parametric marginal proportional hazards mixture cure is parsimonious model for correlated bees survival data.

Analysis of NPK in Camellia sinensis, Gliricidia sepium, and Musa acuminata Biomasses for Preparation of an Organic Fertilizers Formula for Young Tea Plants (Musa acuminata) and Studying of Their Nutrient Release Capacity in the Biodegradation Process

This study investigates the nitrogen (N), phosphorous (P), and potassium (K) contents in raw biomasses of Camellia sinensis, Gliricidia sepium, and Musa acuminata. Therein, the highest N and P content was seen in Camellia sinensis 116.80 ± 0.08 mg and 66.00 ± 0.14 mg respectively. The highest K content (106.80 ± 0.04 mg) was observed in Musa acuminata. Next, all three types of plant materials were allowed to decompose in water for 3 weeks, and a sample from each was analyzed for NPK after the 1st, 2nd, and 3rd week during decomposition. A significant increase in the release of N, P, and K by the Camellia sinensis to water (P Musa acuminate were not significantly changed (P > 0.05) over time. The ratio for N:P:K was calculated for raw biomass samples and decomposed samples to find the best fitting N:P:K ratio to apply to young tea plants as organic fertilizers. In addition to that, the microbial insight of these organic compounds was analyzed by observing how microbial population increased with decomposition by the enumeration of the total microbial count. A considerable increment in total microbial count was observed up to 3.28 × 106, 1.21 × 1010, 2.18 × 108, and 6.49 × 107 CFU/ml for Camellia sinensis, Gliricidia sepium, Musa accuminata (leaves), and Musa accuminata (trunk) respectively. The presence of phosphate solubilizing bacteria (PSB) and nitrogen solubilizing bacteria (NSB) throughout the decomposition period was confirmed by their growth on NBRIP and a modified nutrient medium that was specifically designed for the identification of ammonifiers respectively. Prepared fertilizer samples were applied to young tea plants that were grown in the Mawanella area in Sri Lanka (7°15'12.42"N 80°26'47.62"E) and according to the results, it is clear that fertilizer mixture 1 (N:P:K, 10:5:10, tea dust + Gliricidia + banana trunk) and fertilizer mixture 2 (N:P:K, 10:5:10, tea dust + Gliricidia + banana leaves) has the potential to increase the growth of young tea plants.

Comparison of Semi-Parametric Shared Frailty Models for Bees’Survival

Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.

Clinical characteristics and outcome of autoimmune pancreatitis based on serum immunoglobulin G4 level:A single-center,retrospective cohort study

BACKGROUND Autoimmune pancreatitis(AIP)has been linked with elevated immunoglobulin(Ig)G4 levels.The characteristics and outcomes of AIP based on serum markers have not been fully evaluated.AIM To compare clinical features,treatment efficacy,and outcome of AIP based on serum IgG4 levels and analyze predictors of relapse.METHODS A total of 213 patients with AIP were consecutively reviewed in our hospital from 2006 to 2021.According to the serum IgG4 level,all patients were divided into two groups,the abnormal group(n=148)with a high level of IgG4[>2×upper limit of normal(ULN)]and the normal group(n=65).The t-test or Mann-Whitney U test was used to compare continuous variables.Categorical parameters were compared by theχ^(2) test or Fisher’s exact test.Kaplan-Meier curves Zhou GZ et al.Clinical characteristics and outcome of AIP WJG https://www.wjgnet.com 5126 September 21,2023 Volume 29 Issue 35 and log-rank tests were established to assess the cumulative relapse rates.Univariate and multivariate analyses were used to investigate potential risk factors of AIP relapse.RESULTS Compared with the normal group,the abnormal group had a higher average male age(60.3±10.4 vs 56.5±12.9 years,P=0.047);higher level of serum total protein(72.5±7.9 g/L vs 67.2±7.5 g/L,P<0.001),IgG4(1420.5±1110.9 mg/dL vs 252.7±106.6 mg/dL,P<0.001),and IgE(635.6±958.1 IU/mL vs 231.7±352.5 IU/mL,P=0.002);and a lower level of serum complement C3(100.6±36.2 mg/dL vs 119.0±45.7 mg/dL,P=0.050).In addition,a lower number of cases with abnormal pancreatic duct and pancreatic atrophy(23.6%vs 37.9%,P=0.045;1.6%vs 8.6%,P=0.020,respectively)and a higher rate of relapse(17.6%vs 6.2%,P=0.030)were seen in the abnormal group.Multivariate analyses revealed that serum IgG4[(>2×ULN),hazard ratio(HR):3.583;95%confidence interval(CI):1.218–10.545;P=0.020]and IgA(>1×ULN;HR:5.908;95%CI:1.199–29.120;P=0.029)and age>55 years(HR:2.383;95%CI:1.056–5.378;P=0.036)were independent risk factors of relapse.CONCLUSION AIP patients with high IgG4 levels have clinical features including a more active immune system and higher relapse rate.Several factors,such as IgG4 and IgA,are associated with relapse.