This paper presents a novel approach to identify local determinants of the spatial distribution of international immigrants in big cities. The methodology is based on Bayesian spatial analysis, and it is applied to assess the association of a wide range of variables with the location of the main migrant groups in the Barcelona County. The proposed Bayesian modeling strategy allows addressing spatial dependency and feature selection. Overall, the analysis suggests that factors such as distance from the city center, the proportion of rental housing, and access to public transportation account for much of the variation in location choice. However, these factors exhibit varying effects across different immigrant groups, underscoring the heterogeneous nature of settlement patterns. The findings offer valuable insights for urban policymakers seeking to address the challenges posed by immigration in big cities and to design effective integration strategies.

Statistical Process Control (SPC) is traditionally based on a two-phase framework: a reference sample is required to estimate in-control parameters (Phase I) before active monitoring (Phase II) begins. However, in many contemporary industrial and service settings, such a sample is either unavailable or heavily contaminated by heterogeneity, structural changes, or sporadic anomalies. Under these conditions, classical Phase I and Phase II schemes are difficult to justify. This challenge arose while attempting to remotely monitor industrial printers, prompting a search for alternatives that led to the Bayesian outlier framework proposed by Box and Tiao. This article revisits that framework and argues that its core principles provide a coherent basis for SPC when reliable Phase I data are absent. In the Box and Tiao formulation, observations arise from a mixture of two components sharing a common mean but differing in dispersion; this allows for simultaneous parameter estimation and outlier identification through posterior probabilities. Using the industrial printer case as a primary example, this article demonstrates how this logic can be extended from the original Normal distribution to Poisson data - such as error counts - which are frequently encountered in SPC applications.

When mapping relative mortality risk under specific causes of death in time, one can use small areas and single year mortality data to explore the space time variation in detail. To reduce the variability of the initial mortality risk estimates and help explain their differences, hierarchical Poisson models are typically used. Here we deal with the situation where besides aggregated small-area level data necessary for that, one also has complete individual level data about the presence of certain risk factors in the population, which is now rare but it should become routine in places with universal health coverage using a medical record sharing system. In particular, we consider the convenience of including individual level covariates in the models, and mapping relative mortality risk adjusted for them. That is illustrated by exploring how mortality due to acute myocardial infarction varies in space and in time in Catalonia between 2014 and 2019 using individual data on obesity, diabetes, dyslipidemia and smoking habits.

Purpose: To estimate the incidence of neodymium-doped yttrium aluminum garnet laser (Nd:YAG) capsulotomy up to five years after cataract surgery with different single-piece acrylic monofocal IOLs in a Spanish cohort. Patients and Methods: Data were extracted from electronic medical records. Eligible participants were aged >= 65, had cataract and Zeiss Asphina), and more than six months baseline data. Participants were followed up to five years from surgery and up to six months from Nd:YAG. The incidence of Nd:YAG was compared between the IOLs and multivariate analyses were conducted to identify predictors of Nd:YAG incidence at five-years after cataract surgery. Results: The initial cohort included 9545 patients with 14,519 eyes (53% female, average age 75 years). Of those, 3955 eyes were available for analysis five years after cataract surgery. Throughout the five years post-surgery, Nd:YAG incidence was consistently lower with Alcon Acrysof IOLs than the other IOLs. At five years the Nd:YAG incidence rate for Alcon Acrysof was 8.8%. In comparison, the incidence was 47.4% for AJL LLASY60 (OR = 9.54, 95% CI [6.57, 13.84]), 44.3% for Zeiss Asphina (OR = 8.35, 95% CI [5.85, 11.94]) and 44.0% for IOL Tech Stabibag (OR = 8.02, 95% CI [4.60, 13.84]). Conclusion: Alcon AcrySof IOLs have a consistently lower risk of Nd:YAG incidence over a long follow-up period after cataract surgery, highlighting the importance of IOL choice for patients' long-term outcomes.

We use a Bayesian spatio-temporal model, first to smooth small-area initial life expectancy estimates in Barcelona for 2020, and second to predict what small-area life expectancy would have been in 2020 in absence of covid-19 using mortality data from 2007 to 2019. This allows us to estimate and map the small-area life expectancy loss, which can be used to assess how the impact of covid-19 varies spatially, and to explore whether that loss relates to underlying factors, such as population density, educational level, or proportion of older individuals living alone. We find that the small-area life expectancy loss for men and for women have similar distributions, and are spatially uncorrelated but positively correlated with population density and among themselves. On average, we estimate that the life expectancy loss in Barcelona in 2020 was of 2.01 years for men, falling back to 2011 levels, and of 2.11 years for women, falling back to 2006 levels.

Remotely monitoring industrial printers for an unexpected increase of warning and error messages reduces equipment downtime and increases customer satisfaction. Directly tracking raw error messages rates during a given observation period poses some issues. Firstly, when a printer has not been used much during the observation period, its actual printing time is low. In this situation, even a small set of error messages can become an unexpectedly large rate of messages per printing hour. Secondly, classifying printers in error messages groups based on their rate (for instance, low, medium and high) and studying group changes over time, is useful in identifying potential problems. To overcome these issues, a nonparametric estimation method which simultaneously obtains empirical Bayes estimations of error messages rates and the number of error messages groups is used. This approach has been used in epidemiology, mainly in disease mapping research, but not in an industrial reliability context. The objective of our work is to show the application of the mixture model to real-time monitoring of printers’ error message rates in a way that addresses the two issues mentioned above.

PDF file - 105K, Normal B-cell types signatures used in the GSEA analysis

PDF file - 198K, Recurrent mutations in rearrangements utilizing the six most frequent IGHV genes. Individual codons are represented in the X-axis. Each color represents a different amino acid (AA) change. CDR: complementary determining region, FR: framework region

PDF file - 75K, IGHV, IGHD and IGHJ gene frequencies according to mutational status

PDF file - 332K, Determination of the best cut-off for the percentage of identity of IGHV gene in relation to overall survival. Two cut-offs, 96.6 and 97%, were selected according to a maximally log-rank statistic

PDF file - 105K, Biological processes and genes differentially expressed among M-MCL (M) and U-MCL (U) validated genes by qPCR

The analysis of time series studies linking daily counts of a health indicator with environmental variables (e.g., mortality or hospital admissions with air pollution concentrations or temperature; or motor vehicle crashes with temperature) is usually conducted with Poisson regression models controlling for long-term and seasonal trends using temporal strata. When the study includes multiple zones, analysts usually apply a two-stage approach: first, each zone is analyzed separately, and the resulting zone-specific estimates are then combined using meta-analysis. This approach allows zone-specific control for trends. A one-stage approach uses spatio-temporal strata and could be seen as a particular case of the case–time series framework recently proposed. However, the number of strata can escalate very rapidly in a long time series with many zones. A computationally efficient alternative is to fit a conditional Poisson regression model, avoiding the estimation of the nuisance strata. To allow for zone-specific effects, we propose a conditional Poisson regression model with a random slope, although available frequentist software does not implement this model. Here, we implement our approach in the Bayesian paradigm, which also facilitates the inclusion of spatial patterns in the effect of interest. We also provide a possible extension to deal with overdispersed data. We first introduce the equations of the framework and then illustrate their application to data from a previously published study on the effects of temperature on the risk of motor vehicle crashes. We provide R code and a semi-synthetic dataset to reproduce all analyses presented.

PDF file - 108K, P-values of the 518 genes differentially expressed between M-MCL and U-MCL

Supplementary Figure 2 from MicroRNA Expression, Chromosomal Alterations, and Immunoglobulin Variable Heavy Chain Hypermutations in Mantle Cell Lymphomas

PDF file - 73K, SOX11 expression evaluated by three different techniques. One-hundred-sixty-one MCL patients were studied, 64 by immunohistochemistry (IHC), 143 by quantitative PCR (qPCR) and 50 by gene expression profiling (GEP). Several samples were evaluated with more than one technique, and 8 patients were assessed by all three methodologies. The results were concordant in all cases

ObjectiveTo assess whether alcohol intake is associated with the onset of migraine attacks up to 2 days after consumption in individuals with episodic migraine (EM). BackgroundAlthough alcohol has long been suspected to be a common migraine trigger, studies have been inconclusive in proving this association. MethodsThis was an observational prospective cohort study among individuals with migraine who registered to use a digital health platform for headache. Eligible individuals were aged >= 18 years with EM who consumed alcohol and had tracked their headache symptoms and alcohol intake for >= 90 days. People who did not drink any alcohol were excluded. The association of alcohol intake ("Yes/No") and of the number of alcoholic beverages in the 2 days preceding a migraine attack was assessed accounting for the presence of migraine on day-2 and its interaction with alcohol intake on day-2, and further adjusted for sex, age, and average weekly alcohol intake. ResultsData on 487 individuals reporting 5913 migraine attacks and a total of 40,165 diary days were included in the analysis. Presence of migraine on day-2 and its interaction with alcohol intake on day-2 were not significant and removed from the model. At the population level, alcohol intake on day-2 was associated with a lower probability of migraine attack (OR [95% CI] = 0.75 [0.68, 0.82]; event rate 1006/4679, 21.5%), while the effect of alcohol intake on day-1 was not significant (OR [95% CI] = 1.01 [0.91, 1.11]; event rate 1163/4679, 24.9%) after adjusting for sex, age, and average weekly alcohol intake. Similar results were obtained with the number of beverages as exposure. ConclusionsIn this English-speaking cohort of individuals with EM who identified themselves as mostly low-dose alcohol consumers, there was no significant effect on the probability of a migraine attack in the 24 h following consumption, and a slightly lower likelihood of a migraine attack from 24 to 48 h following use.

Purpose: To estimate the economic impact of neodymium-doped yttrium aluminum garnet (Nd:YAG) laser capsulotomy and its related complications for five different intraocular lenses (IOLs) from the payer and hospital perspectives in Spain. Materials and Methods: The three-year incidence rates of Nd:YAG laser capsulotomy after cataract surgery with five different single-piece acrylic monofocal IOLs (AcrySof IOLs, AJL LLASY60, IOLTech Stabibag, Medicontur Bi-flex, Zeiss Asphina) for 8293 patients were derived from odds ratios of multivariate analysis adjusted for age, gender, and diabetic retinopathy. A cost-consequence model for a hypothetical cohort of 2000 eyes was then developed to quantify the potential impact of Nd:YAG capsulotomy in terms of costs and time for each of the included IOLs, from the payer and hospital perspectives. Results: The adjusted three-year Nd:YAG laser capsulotomy incidence was 5.0% (95% CI 3.9 to 6.1) for AcrySof and ranged from 26.0% to 44.0% for the other four IOLs. The average costs of Nd:YAG treatment and related complications were €261.90 for payers and €19.99 for hospitals. The average time needed for Nd:YAG treatment and related complications was 32.82 minutes. Model estimates based on 2000 hypothetical cataract surgeries showed that AcrySof IOLs could lead to cost savings between €110,259.90 and €205,591.50 for payers. For hospitals, time, and cost savings with AcrySof ranged from 230.29 hours and €8415.79 compared to Zeiss Asphina to 429.40 hours and €15,692.15 compared to AJL LLASY60 IOLs. Conclusion: Post cataract surgery, AcrySof IOLs were associated with a significantly lower incidence of Nd:YAG treatment and its subsequent complications compared to other IOLs. Our analysis shows that IOL choice is an important factor that can reduce the burden for patients, payers, and hospitals.

Purpose:To estimate the economic impact of neodymium-doped yttrium aluminum garnet (Nd:YAG) laser capsulotomy and its related complications for five different intraocular lenses (IOLs) from the payer and hospital perspectives in Spain.Materials and Methods:The three-year incidence rates of Nd:YAG laser capsulotomy after cataract surgery with five different single-piece acrylic monofocal IOLs (AcrySof IOLs, AJL LLASY60, IOL Tech Stabibag, Medicontur Bi-flex, Zeiss Asphina) for 8293 patients were derived from odds ratios of multivariate analysis adjusted for age, gender, and diabetic retinopathy. A cost-consequence model for a hypothetical cohort of 2000 eyes was then developed to quantify the potential impact of Nd:YAG capsulotomy in terms of costs and time for each of the included IOLs, from the payer and hospital perspectives.Results:The adjusted three-year Nd:YAG laser capsulotomy incidence was 5.0% (95% CI 3.9 to 6.1) for AcrySof and ranged from 26.0% to 44.0% for the other four IOLs. The average costs of Nd:YAG treatment and related complications were €261.90 for payers and €19.99 for hospitals. The average time needed for Nd:YAG treatment and related complications was 32.82 minutes. Model estimates based on 2000 hypothetical cataract surgeries showed that AcrySof IOLs could lead to cost savings between €110,259.90 and €205,591.50 for payers. For hospitals, time, and cost savings with AcrySof ranged from 230.29 hours and €8415.79 compared to Zeiss Asphina to 429.40 hours and €15,692.15 compared to AJL LLASY60 IOLs.Conclusion:Post cataract surgery, AcrySof IOLs were associated with a significantly lower incidence of Nd:YAG treatment and its subsequent complications compared to other IOLs. Our analysis shows that IOL choice is an important factor that can reduce the burden for patients, payers, and hospitals.

To explore whether alcohol intake is associated with onset of migraine attacks up to two days after consumption in individuals with episodic migraine (EM).