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A statistical study of fitting log-normal distributions to air sampling concentrations and random intakes is reported in this paper. An improved method on the approximation of a sum of log-normal distributions to a log-normal distribution is used to forecast bioassay results and their uncertainties. These methods can be used in the design and implementation of air control monitoring and bioassay programs for introducing statistical criteria to determine when a bioassay is required as well as the frequency.

We have addressed whether patients' immune system status after allogeneic stem cell transplantation, assessed more than 1 year after the procedure, recovers normal function as compared with that of their respective donors. An additional aim was to compare the status of the immune system between patients receiving reduced-intensity conditioning regimens and those undergoing myeloablative transplantations. For this purpose, we analyzed not only the different subsets of peripheral blood (PB) lymphocytes, but also circulating dendritic cell (DC) subpopulations, together with cytokine production by PB T cells, in a series of 38 patients undergoing allogeneic stem cell transplantation. We compared these patients with their respective HLA-matched donors by performing a simultaneous patient/donor paired study. Complete bone marrow chimerism status and normal PB cell counts were demonstrated in all recipients. The most relevant numeric differences found between patients and donors were related to the distribution of the distinct subsets of PB DCs (CD16+ DCs were increased, whereas myeloid and plasmacytoid DC subsets were decreased in the patient group). This was associated with an increased number of B cells, an inverted CD4/CD8 T-cell ratio, and a decrease in CD4+/CD8+ double-positive T cells in the patient group. In addition, a predominance of a T-helper 1 pattern of cytokine production (interferon γ and tumor necrosis factor α) with decreased secretion of T-helper 2-associated cytokines (interleukin 5 and interleukin 10) was also observed at the single-cell level. No significant differences were found in any of the parameters analyzed between patients receiving reduced-intensity conditioning regimens and those undergoing myeloablative transplantations.

We tested the principle of whether patient long-term hematopoiesis following allogeneic stem cell transplantation (allo-SCT) reflects the characteristics of the hematopoiesis of their respective donor. For this purpose, we analyzed bone marrow (BM) hematopoiesis using long-term cultures (LTC), delta assays, and clonogeneic assays as well as CD34 + cells and their subsets by flow cytometry in a series of 37 patients undergoing allo-SCT, and we compared it to that of their respective human leukocyte antigen–matched sibling donors in a paired study performed more than 1 year after the transplant procedure. Interestingly, the main factor that influenced post-allo-SCT BM hematopoiesis in the long term was donor hematopoiesis. Nevertheless, compared to their respective donors, patients exhibited a significantly lower number of colony-forming units granulomonocytic, burst-forming units erythroid, and immature progenitors (CD34 ++ /CD38 dim /CD90 + /CD133 + cells, LTC-initiating cells, and colonies generated in the delta assay). Moreover, BM stromal function was diminished in patients undergoing allo-SCT compared to their donors. In addition, the presence of chronic graft-versus-host disease under immunosuppressive treatment also conditioned an impaired hematopoietic function. In summary, our study shows that BM hematopoiesis evaluated more than 1 year after an allo-SCT mainly reproduces that of their respective donors, although with a significantly decreased in vitro activity.

In this paper we study the problem of designing experiments for nonlinear regression models in pharmacokinetics. In particular, we consider an extension of the popular Michaelis-Menten model (MMM) with the addition of a linear term. D-optimal designs supported at 3 points with equal weights are calculated for the MMM extension using the general equivalence theorem. This model is a special case of partially nonlinear regression. We obtain c-, D-optimal designs for estimating the three parameters of the model. Next we calculate compound designs. Some numerical examples are provided with efficiencies for estimating each of the parameters.

Using the characteristic polynomial coefficients of the inverse of the information matrix, design criteria can be defined between A- and D-optimality (Lopez-Fidalgo and Rodriguez-Diaz, 1998). With a slight modification of the classical algorithms, the gradient expression allows us to find some optimal characteristic designs for polynomial regression. We observe that these designs are a smooth transition from A- to D-optimal designs. Moreover, for some of these optimal designs, the efficiencies for both criteria, A- and D-optimality, are quite good.

Minimax designs for logistic regression with one design variable are considered where the design space is a general interval [a, b] on the straight real line. This corresponds to a weighted linear regression model for a specific weight function. Torsney and Lopez-Fidalgo (1995) computed maximum variance (MV-) optimal designs for simple linear regression for a general interval. Lopez-Fidalgo et al. (1998) gave MV-optimal designs for symmetric weight functions and symmetric intervals, [-b, b]. Computations for general intervals for logistic regression are much more complex. Using similar approaches to these two papers and the equivalence theorem, explicit minimax optimal designs are given for different regions of points (a, b) in the semi-plane b>a for the logistic model. This complements Dette and Sahm (1998) who give a method for computing MV-optimal designs without any restriction on the design space. From this, Standardized Maximum Variance (SMV-) optimal designs immediately follow. The same approach could be used for probit, double exponential, double reciprocal and some other popular models in the biomedical sciences.

In this paper, we investigate the robustness properties of minimax designs for binary models. We focus on SMV and MV-optimal designs for the logistic and double exponential models and report on the efficiency changes in both types of designs when the nominal values of the parameters are misspecified.

The criterion of the largest of the variances of the parameter estimates in a model is a difficult, but meaningful criterion to use. In this paper weighted linear regression is considered for some standard symmetric weight functions. Conditions of MV-optimality are given for any weight function. The optimal design is found for any symmetric interval for some weight functions. The equivalence theorem is used for this purpose.

Many optimality criteria have been used in the literature of experimental design. Two of the most common are A-optimality and D-optimality. They are the first and the last coefficients of the characteristic polynomial of the inverse information matrix. In this paper, criteria from the remaining coefficients are considered, and some properties are studied. While A-optimality focuses on the average of the estimate variances and D-optimality focuses on all of the covariances, these criteria take into consideration the covariances considered in groups of two, three, four,…

Background The pathology of the Benign Paroxysmal Positional Vertigo (BPPV) is detected by a clinician through maneuvers consisting of a series of consecutive head turns that trigger the symptoms of vertigo in patient. A statistical model based on a new maneuver has been developed in order to calculate the volume of endolymph displaced after the maneuver. Methods A simplification of the Navier‐Stokes problem from the fluids theory has been used to construct the model. In addition, the same cubic splines that are commonly used in kinematic control of robots were used to obtain an appropriate description of the different maneuvers. Then experimental designs were computed to obtain an optimal estimate of the model. Results D‐optimal and c‐optimal designs of experiments have been calculated. These experiments consist of a series of specific head turns of duration Δt and angle α that should be performed by the clinician on the patient. The experimental designs obtained indicate the duration and angle of the maneuver to be performed as well as the corresponding proportion of replicates. Thus, in the D‐optimal design for 100 experiments, the maneuver consisting of a positive 30° pitch from the upright position, followed by a positive 30° roll, both with a duration of one and a half seconds is repeated 47 times. Then the maneuver with 60° /6° pitch/roll during half a second is repeated 16 times and the maneuver 90° /90° pitch/roll during half a second is repeated 37 times. Other designs with significant differences are computed and compared. Conclusions A biomechanical model was derived to provide a quantitative basis for the detection of BPPV. The robustness study for the D‐optimal design, with respect to the choice of the nominal values of the parameters, shows high efficiencies for small variations and provides a guide to the researcher. Furthermore, c‐optimal designs give valuable assistance to check how efficient the D‐optimal design is for the estimation of each of the parameters. The experimental designs provided in this paper allow the physician to validate the model. The authors of the paper have held consultations with an ENT consultant in order to align the outline more closely to practical scenarios.

MV-optimality is a potentially difficult criterion because of its nondifferentiability at equal variance designs. However in many cases such designs can be easily determined. In this paper MV-optimum designs for simple linear regression are found. The equivalence theorem of and the directional derivative of the MV-criterion derived by Ford I., (3), have been used for this purpose. It turns out that for simple linear regression there exist an MV-optimal design with a support of at most two points. Such designs could be of a wide ranging practical value.

La prevalencia de disfunciones sexuales en el alcoholismo es alta y oscila, segun distintos estudios, entre el 3,2 % y el 64,4 %. El presente estudio tiene como objetivo investigar la frecuencia de este tipo de alteraciones en una muestra de pacientes alcoholicos que estaban en tratamiento por esta enfermedad. Asi mismo, se pretende averiguar los factores que pueden influir en su genesis, ademas del alcohol. La muestra de estudio comprendia 183 personas, 150 varones y 33 mujeres cuya edad media era de 43 anos. Se administro a los pacientes una encuesta autoaplicada y anonima que contenia el Cuestionario de Funcionamiento Sexual de LoPiccolo (SHF). Asi mismo se determinaron los niveles de testosterona, estradiol y prolactina. Los resultados principales fueron: el funcionamiento sexual global era aceptable (puntuacion global: 0,415 ± 0,155) y significativamente mejor en los varones que en las mujeres; el 45% mantenia relaciones semanalmente, el 69% experimentaba deseo sexual durante la semana, el 81% de los varones no tenia problemas en alcanzar y mantener la ereccion y el 10% referia eyaculacion precoz; en el grupo de mujeres, el 10% referia vaginismo y el 5% dolor en el coito. Los niveles de testosterona, estradiol y prolactina estaban en el rango normal; ni el diagnostico, ni la cantidad de gramos de alcohol consumido, ni la situacion de abstinencia o consumo influia en el funcionamiento sexual global. La presencia de enfermedades somaticas y la ingestion de medicamentos, principalmente Cianamida calcica, empeoraban significativamente el funcionamiento sexual global.

In many experiments, not all explanatory variables can be controlled. When the units arise sequentially, different approaches may be used. The authors study a natural sequential procedure for "mar- ginally restricted" D-optimal designs. They assume that one set of explanatory variables (xi) is observed sequentially, and that the experimenter responds by choosing an appropriate value of the explanatory vari- able X2. In order to solve the sequential problem a priori, the authors consider the problem of constructing optimal designs with a prior marginal distribution for xi. This eliminates the influence of units already observed on the next unit to be designed. They give explicit designs for various cases in which the mean re- sponse follows a linear regression model; they also consider a case study with a nonlinear logistic response. They find that the optimal strategy often consists of randomizing the assignment of the values of X2. Plans sequentiels D-optimaux sous contraintes marginales Resume : Dans bien des experiences, on ne peut pas controler toutes les variables explicatives. Lorsque les unites arrivent sequentiellement, diverses approches sont possibles. Les auteurs etudient une procedure se- quentielle naturelle pour les plans D-optimaux sous "contraintes marginales." Ils supposent qu'un ensemble de variables explicatives (xi) est observe sequentiellement et que l'experimentateur reagit en choisissant un niveau approprie pour la variable explicative xi. Pour resoudre ce probleme sequentiel a priori, les auteurs proposent la construction de plans optimaux etant donne une loi a priori marginale pour xi. Ceci a pour