Effects of air pollution on asthma hospitalization rates in different age groups in metropolitan cities of Korea

Many studies have shown relationships between air pollution and the rate of hospital admissions for asthma. A few studies have controlled for age-specific effects by adding separate smoothing functions for each age group. However, it has not yet been reported whether air pollution effects are significantly different for different age groups. This lack of information is the motivation for this study, which tests the hypothesis that air pollution effects on asthmatic hospital admissions are significantly different by age groups. Each air pollutant's effect on asthmatic hospital admissions by age groups was estimated separately. In this study, daily time-series data for hospital admission rates from seven cities in Korea from June 1999 through 2003 were analyzed. The outcome variable, daily hospital admission rates for asthma, was related to five air pollutants which were used as the independent variables, namely particulate matter <10 micrometers (μm) in aerodynamic diameter (PM10), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Meteorological variables were considered as confounders. Admission data were divided into three age groups: children (<15 years of age), adults (ages 15-64), and elderly (≥ 65 years of age). The adult age group was considered to be the reference group for each city. In order to estimate age-specific air pollution effects, the analysis was separated into two stages. In the first stage, Generalized Additive Models (GAMs) with cubic spline for smoothing were applied to estimate the age-city-specific air pollution effects on asthmatic hospital admission rates by city and age group. In the second stage, the Bayesian Hierarchical Model with non-informative prior which has large variance was used to combine city-specific effects by age groups. The hypothesis test showed that the effects of PM10, CO and NO2 were significantly different by age groups. Assuming that the air pollution effect for adults is zero as a reference, age-specific air pollution effects were: -0.00154 (95% confidence interval(CI)= (-0.0030,-0.0001)) for children and 0.00126 (95% CI = (0.0006, 0.0019)) for the elderly for PM 10; -0.0195 (95% CI = (-0.0386,-0.0004)) for children for CO; and 0.00494 (95% CI = (0.0028, 0.0071)) for the elderly for NO2. Relative rates (RRs) were 1.008 (95% CI = (1.000-1.017)) in adults and 1.021 (95% CI = (1.012-1.030)) in the elderly for every 10 μg/m3 increase of PM10 , 1.019 (95% CI = (1.005-1.033)) in adults and 1.022 (95% CI = (1.012-1.033)) in the elderly for every 0.1 part per million (ppm) increase of CO; 1.006 (95%CI = (1.002-1.009)) and 1.019 (95%CI = (1.007-1.032)) in the elderly for every 1 part per billion (ppb) increase of NO2 and SO2, respectively. Asthma hospital admissions were significantly increased for PM10 and CO in adults, and for PM10, CO, NO2 and SO2 in the elderly.^

Does prior receipt of a rifamycin antibiotic increase the risk of acquiring an infection due to a rifamycin-resistant strain of Clostridium difficile?

Objectives. To examine the association between prior rifamycin exposure and later development of C. difficile infection (CDI) caused by a rifamycin-resistant strain of C. difficile , and to compare patient characteristics between rifamycin-resistant strains of C. difficile infection and rifamycin-susceptible strains of C. difficile infection. ^ Methods. A case-control study was performed in a large university-affiliated hospital in Houston, Texas. Study subjects were patients with C. difficile infection acquired at the hospital with culture-positive isolates of C. difficile with which in vitro rifaximin and rifampin susceptibility has been tested. Prior use of rifamycin, demographic and clinical characteristics was compared between case and control groups using univariate statistics. ^ Results. A total of 49 C. difficile strains met the study inclusion criteria for rifamycin-resistant case isolates, and a total of 98 rifamycin-susceptible C. difficile strains were matched to case isolates. Of 49 case isolates, 12 (4%) were resistant to rifampin alone, 12 (4%) were resistant to rifaximin alone, and 25 (9%) were resistant to both rifampin and rifaximin. There was no significant association between prior rifamycin use and rifamycin-resistant CDI. Cases and controls did not differ according to demographic characteristics, length of hospital stay, known risk factors of CDI, type of CDI-onset, and pre-infection medical co-morbidities. Our results on 37 rifaximin-resistant isolates (MIC ≥32 &mgr;g/ml) showed more than half of isolates had a rifaximin MIC ≥256 &mgr;g/ml, and out of these isolates, 19 isolates had MICs ≥1024 &mgr;g/ml. ^ Conclusions. Using a large series of rifamycin-non-susceptible isolates, no patient characteristics were independently associated with rifamycin-resistant CDI. This data suggests that factors beyond previous use of rifamycin antibiotics are primary risk factors for rifamycin-resistant C. difficile. ^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

A Logarithmic Image Prior for Blind Deconvolution

Blind Deconvolution consists in the estimation of a sharp image and a blur kernel from an observed blurry image. Because the blur model admits several solutions it is necessary to devise an image prior that favors the true blur kernel and sharp image. Many successful image priors enforce the sparsity of the sharp image gradients. Ideally the L0 “norm” is the best choice for promoting sparsity, but because it is computationally intractable, some methods have used a logarithmic approximation. In this work we also study a logarithmic image prior. We show empirically how well the prior suits the blind deconvolution problem. Our analysis confirms experimentally the hypothesis that a prior should not necessarily model natural image statistics to correctly estimate the blur kernel. Furthermore, we show that a simple Maximum a Posteriori formulation is enough to achieve state of the art results. To minimize such formulation we devise two iterative minimization algorithms that cope with the non-convexity of the logarithmic prior: one obtained via the primal-dual approach and one via majorization-minimization.

Probabilistic mapping with mobile robots in structured environments

La mayor parte de los entornos diseñados por el hombre presentan características geométricas específicas. En ellos es frecuente encontrar formas poligonales, rectangulares, circulares . . . con una serie de relaciones típicas entre distintos elementos del entorno. Introducir este tipo de conocimiento en el proceso de construcción de mapas de un robot móvil puede mejorar notablemente la calidad y la precisión de los mapas resultantes. También puede hacerlos más útiles de cara a un razonamiento de más alto nivel. Cuando la construcción de mapas se formula en un marco probabilístico Bayesiano, una especificación completa del problema requiere considerar cierta información a priori sobre el tipo de entorno. El conocimiento previo puede aplicarse de varias maneras, en esta tesis se presentan dos marcos diferentes: uno basado en el uso de primitivas geométricas y otro que emplea un método de representación cercano al espacio de las medidas brutas. Un enfoque basado en características geométricas supone implícitamente imponer un cierto modelo a priori para el entorno. En este sentido, el desarrollo de una solución al problema SLAM mediante la optimización de un grafo de características geométricas constituye un primer paso hacia nuevos métodos de construcción de mapas en entornos estructurados. En el primero de los dos marcos propuestos, el sistema deduce la información a priori a aplicar en cada caso en base a una extensa colección de posibles modelos geométricos genéricos, siguiendo un método de Maximización de la Esperanza para hallar la estructura y el mapa más probables. La representación de la estructura del entorno se basa en un enfoque jerárquico, con diferentes niveles de abstracción para los distintos elementos geométricos que puedan describirlo. Se llevaron a cabo diversos experimentos para mostrar la versatilidad y el buen funcionamiento del método propuesto. En el segundo marco, el usuario puede definir diferentes modelos de estructura para el entorno mediante grupos de restricciones y energías locales entre puntos vecinos de un conjunto de datos del mismo. El grupo de restricciones que se aplica a cada grupo de puntos depende de la topología, que es inferida por el propio sistema. De este modo, se pueden incorporar nuevos modelos genéricos de estructura para el entorno con gran flexibilidad y facilidad. Se realizaron distintos experimentos para demostrar la flexibilidad y los buenos resultados del enfoque propuesto. Abstract Most human designed environments present specific geometrical characteristics. In them, it is easy to find polygonal, rectangular and circular shapes, with a series of typical relations between different elements of the environment. Introducing this kind of knowledge in the mapping process of mobile robots can notably improve the quality and accuracy of the resulting maps. It can also make them more suitable for higher level reasoning applications. When mapping is formulated in a Bayesian probabilistic framework, a complete specification of the problem requires considering a prior for the environment. The prior over the structure of the environment can be applied in several ways; this dissertation presents two different frameworks, one using a feature based approach and another one employing a dense representation close to the measurements space. A feature based approach implicitly imposes a prior for the environment. In this sense, feature based graph SLAM was a first step towards a new mapping solution for structured scenarios. In the first framework, the prior is inferred by the system from a wide collection of feature based priors, following an Expectation-Maximization approach to obtain the most probable structure and the most probable map. The representation of the structure of the environment is based on a hierarchical model with different levels of abstraction for the geometrical elements describing it. Various experiments were conducted to show the versatility and the good performance of the proposed method. In the second framework, different priors can be defined by the user as sets of local constraints and energies for consecutive points in a range scan from a given environment. The set of constraints applied to each group of points depends on the topology, which is inferred by the system. This way, flexible and generic priors can be incorporated very easily. Several tests were carried out to demonstrate the flexibility and the good results of the proposed approach.

Effect of short-term fasting prior to slaughter on welfare and meat quality or rainbow trout (Oncorhynchus mykiss)

El manejo pre-sacrificio es de vital importancia en acuicultura, ya que afecta tanto a las reacciones fisiológicas como a los procesos bioquímicos post mortem, y por tanto al bienestar y a la calidad del producto. El ayuno pre-sacrificio se lleva a cabo de forma habitual en acuicultura, ya que permite el vaciado del aparato digestivo de restos de alimento y heces, reduciendo de esta manera la carga bacteriana en el intestino y la dispersión de enzimas digestivos y potenciales patógenos a la carne. Sin embargo, la duración óptima de este ayuno sin que el pez sufra un estrés innecesario no está clara. Además, se sabe muy poco sobre la mejor hora del día para realizar el sacrificio, lo que a su vez está regido por los ritmos diarios de los parámetros fisiológicos de estrés. Finalmente, se sabe que la temperatura del agua juega un papel muy importante en la fisiología del estrés pero no se ha determinado su efecto en combinación con el ayuno. Además, las actuales recomendaciones en relación a la duración óptima del ayuno previo al sacrificio en peces no suelen considerar la temperatura del agua y se basan únicamente en días y no en grados día (ºC d). Se determinó el efecto del ayuno previo al sacrificio (1, 2 y 3 días, equivalente a 11,1-68,0 grados día) y la hora de sacrificio (08h00, 14h00 y 20h00) en trucha arco iris (Oncorhynchus mykiss) de tamaño comercial en cuatro pruebas usando diferentes temperaturas de agua (Prueba 1: 11,8 ºC; Prueba 2: 19,2 ºC; Prueba 3: 11,1 ºC; y Prueba 4: 22,7 ºC). Se midieron indicadores biométricos, hematológicos, metabólicos y de calidad de la carne. En cada prueba, los valores de los animales ayunados (n=90) se compararon con 90 animales control mantenidos bajo condiciones similares pero nos ayunados. Los resultados sugieren que el ayuno tuvo un efecto significativo sobre los indicadores biométricos. El coeficiente de condición en los animales ayunados fue menor que en los controles después de 2 días de ayuno. El vaciado del aparato digestivo se produjo durante las primeras 24 h de ayuno, encontrándose pequeñas cantidades de alimento después de 48 h. Por otra parte, este vaciado fue más rápido cuando las temperaturas fueron más altas. El peso del hígado de los animales ayunados fue menor y las diferencias entre truchas ayunadas y controles fueron más evidentes a medida que el vaciado del aparato digestivo fue más rápido. El efecto del ayuno hasta 3 días en los indicadores hematológicos no fue significativo. Los niveles de cortisol en plasma resultaron ser altos tanto en truchas ayunadas como en las alimentadas en todas las pruebas realizadas. La concentración media de glucosa varió entre pruebas pero mostró una tendencia a disminuir en animales ayunados a medida que el ayuno progresaba. En cualquier caso, parece que la temperatura del agua jugó un papel muy importante, ya que se encontraron concentraciones más altas durante los días 2 y 3 de ayuno en animales mantenidos a temperaturas más bajas previamente al sacrificio. Los altos niveles de lactato obtenidos en sangre parecen sugerir episodios de intensa actividad muscular pero no se pudo encontrar relación con el ayuno. De la misma manera, el nivel de hematocrito no mostró efecto alguno del ayuno y los leucocitos tendieron a ser más altos cuando los animales estaban menos estresados y cuando su condición corporal fue mayor. Finalmente, la disminución del peso del hígado (índice hepatosomático) en la Prueba 3 no se vio acompañada de una reducción del glucógeno hepático, lo que sugiere que las truchas emplearon una estrategia diferente para mantener constantes los niveles de glucosa durante el periodo de ayuno en esa prueba. En relación a la hora de sacrificio, se obtuvieron niveles más bajos de cortisol a las 20h00, lo que indica que las truchas estaban menos estresadas y que el manejo pre-sacrificio podría resultar menos estresante por la noche. Los niveles de hematocrito fueron también más bajos a las 20h00 pero solo con temperaturas más bajas, sugiriendo que las altas temperaturas incrementan el metabolismo. Ni el ayuno ni la hora de sacrificio tuvieron un efecto significativo sobre la evolución de la calidad de la carne durante los 3 días de almacenamiento. Por el contrario, el tiempo de almacenamiento sí que parece tener un efecto claro sobre los parámetros de calidad del producto final. Los niveles más bajos de pH se alcanzaron a las 24-48 h post mortem, con una lata variabilidad entre duraciones del ayuno (1, 2 y 3 días) en animales sacrificados a las 20h00, aunque no se pudo distinguir ningún patrón común. Por otra parte, la mayor rigidez asociada al rigor mortis se produjo a las 24 h del sacrificio. La capacidad de retención de agua se mostró muy estable durante el período de almacenamiento y parece ser independiente de los cambios en el pH. El parámetro L* de color se incrementó a medida que avanzaba el período de almacenamiento de la carne, mientras que los valores a* y b* no variaron en gran medida. En conclusión, basándose en los resultados hematológicos, el sacrificio a última hora del día parece tener un efecto menos negativo en el bienestar. De manera general, nuestros resultados sugieren que la trucha arco iris puede soportar un período de ayuno previo al sacrificio de hasta 3 días o 68 ºC d sin que su bienestar se vea seriamente comprometido. Es probable que con temperaturas más bajas las truchas pudieran ser ayunadas durante más tiempo sin ningún efecto negativo sobre su bienestar. En cualquier caso, se necesitan más estudios para determinar la relación entre la temperatura del agua y la duración óptima del ayuno en términos de pérdida de peso vivo y la disminución de los niveles de glucosa en sangre y otros indicadores metabólicos. SUMMARY Pre-slaughter handling in fish is important because it affects both physiological reactions and post mortem biochemical processes, and thus welfare and product quality. Pre-slaughter fasting is regularly carried out in aquaculture, as it empties the viscera of food and faeces, thus reducing the intestinal bacteria load and the spread of gut enzymes and potential pathogens to the flesh. However, it is unclear how long rainbow trout can be fasted before suffering unnecessary stress. In addition, very little is known about the best time of the day to slaughter fish, which may in turn be dictated by diurnal rhythms in physiological stress parameters. Water temperature is also known to play a very important role in stress physiology in fish but the combined effect with fasting is unclear. Current recommendations regarding the optimal duration of pre-slaughter fasting do not normally consider water temperature and are only based on days, not degree days (ºC d). The effects of short-term fasting prior to slaughter (1, 2 and 3 days, between 11.1 and 68.0 ºC days) and hour of slaughter (08h00, 14h00 and 20h00) were determined in commercial-sized rainbow trout (Oncorhynchus mykiss) over four trials at different water temperatures (TRIAL 1, 11.8 ºC; TRIAL 2, 19.2 ºC; TRIAL 3, 11.1 ºC; and TRIAL 4, 22.7 ºC). We measured biometric, haematological, metabolic and product quality indicators. In each trial, the values of fasted fish (n=90) were compared with 90 control fish kept under similar conditions but not fasted. Results show that fasting affected biometric indicators. The coefficient of condition in fasted trout was lower than controls 2 days after food deprivation. Gut emptying occurred within the first 24 h after the cessation of feeding, with small traces of digesta after 48 h. Gut emptying was faster at higher water temperatures. Liver weight decreased in food deprived fish and differences between fasted and fed trout were more evident when gut clearance was faster. The overall effect of fasting for up to three days on haematological indicators was small. Plasma cortisol levels were high in both fasted and fed fish in all trials. Plasma glucose response to fasting varied among trials, but it tended to be lower in fasted fish as the days of fasting increased. In any case, it seems that water temperature played a more important role, with higher concentrations at lower temperatures on days 2 and 3 after the cessation of feeding. Plasma lactate levels indicate moments of high muscular activity and were also high, but no variation related to fasting could be found. Haematocrit did not show any significant effect of fasting, but leucocytes tended to be higher when trout were less stressed and when their body condition was higher. Finally, the loss of liver weight was not accompanied by a decrease in liver glycogen (only measured in TRIAL 3), suggesting that a different strategy to maintain plasma glucose levels was used. Regarding the hour of slaughter, lower cortisol levels were found at 20h00, suggesting that trout were less stressed later in the day and that pre-slaughter handling may be less stressful at night. Haematocrit levels were also lower at 20h00 but only at lower temperatures, indicating that higher temperatures increase metabolism. Neither fasting nor the hour of slaughter had a significant effect on the evolution of meat quality during 3 days of storage. In contrast, storage time seemed to have a more important effect on meat quality parameters. The lowest pH was reached 24-48 h post mortem, with a higher variability among fasting durations at 20h00, although no clear pattern could be discerned. Maximum stiffening from rigor mortis occurred after 24 h. The water holding capacity was very stable throughout storage and seemed to be independent of pH changes. Meat lightness (L*) slightly increased during storage and a* and b*-values were relatively stable. In conclusion, based on the haematological results, slaughtering at night may have less of a negative effect on welfare than at other times of the day. Overall, our results suggest that rainbow trout can cope well with fasting up to three days or 68 ºC d prior to slaughter and that their welfare is therefore not seriously compromised. At low water temperatures, trout could probably be fasted for longer periods without negative effects on welfare but more research is needed to determine the relationship between water temperature and days of fasting in terms of loss of live weight and the decrease in plasma glucose and other metabolic indicators.

Commentaria in Psalmos Davidicos, prisci cuiusdam auctoris incogniti in duos divisa tomos : hic prior expositionem à primo Psalmo vsque ad LXXXVIII...

Autor tomado de CCPB

Commentaria in Psalmos Dauidicos, prisci cuiusdam auctoris incogniti : in duos diuisa tomos : hic prior expositionem à primo Psalmo vsque ad LXXXVIII, posterior reliquorum complectitur

Autor: Michele Angriani tomado de Adams

Pauli Soncinatis epitomes quaestionum Ioanis Capreoli, super libros sententiarum : pars prior complectens libr. I [et] II [-pars altera, complectens librum tertium, [et] quartum] / per F. Isidorum de Isolanis Mediolanen sem edita multis in locis suppleta

Nunc demum in hac postrema editione accuratissime recognita [et] emendatius quam antea excusa

Pauli Soncinatis epitomes quaestionum Ioanis Capreoli, super libros sententiarum : pars prior complectens libr. I [et] II [-pars altera, complectens librum tertium, [et] quartum] / per F. Isidorum de Isolanis Mediolanen sem edita multis in locis suppleta

Nunc demum in hac postrema editione accuratissime recognita [et] emendatius quam antea excusa

Philonis Iudaei, ... Operum, quotquot ad hunc diem haberi potuerunt, tomus prior-[alter] / interprete, Sigismundo Gelenio, Ioanne Christophorsno & Ioanne Voeuroeo.

Sign.: *4, a-z8, 2a-2l8, 2m4; A-Z8, 2A-2H8

Fundación de la real iglesia parroquial única de Santa María de Ujué, y breve noticia de los dones y privilegios con que la han distinguido los reyes de Navarra / por el prior cura párroco de la misma villa José Guillermo Lacunza.

2a ed.