Journal of Biometrics & Biostatistics

Hemoglobin is a unique protein, which is responsible for oxygen and carbon dioxide transportation all the body. The protein location is inside the erythrocytes and the special oval shape makes it easily pass through blood walls to supply oxygen to the tissues and organs. It is supposed that the hemoglobin amount could change depending on the person`s age, gender or nationality. We designed a research to see the molecular differences among Bosnian and Turkish young person`s whose age interval is 18-23 and old person`s age interval is 43-65. Totally 300 person`s, 50 from each Bosnian/ Turkish Female/Male and 50 old male and 50 old female were selected for the research. The students` the hemoglobin amount has been recorded individually and presented in a table. As a result of the measurement, The Turkish females average has the lowest hemoglobin Turkish males average shows the maximum amount of hemoglobin, 12.01 g/dl and 14.65 g/dl respectively. When the female gets older their the hemoglobin amount increase in their blood, 7.3% in Bosnian and 12.2% in Turkish. On the other side, the male blood the hemoglobin amount is almost similar by aging, Bosnian male hemoglobin just increase 0.74%, but in Turkish male 1.3% decrease. The result shows that female the hemoglobin amount is affected by age more than male.

We consider confidence interval estimation for a binomial proportion when the data have already been observed and x, the observed number of successes in a sample of size n, is zero. In this case, the main objective of the investigator is usually to obtain a reasonable upper bound for the true probability of success, i.e., the upper limit of a one-sided confidence interval. In this article, we use observed interval length and p-confidence to evaluate eight methods for finding the upper limit of a confidence interval for a binomial proportion when x is known to be zero. Long-run properties such as expected interval length and coverage probability are not applicable because the sample data have already been observed. We show that many popular approximate methods that are known to have good long-run properties in the general setting perform poorly when x=0 and recommend that the Clopper-Pearson exact method be used instead.

Biomolecules and particularly proteins and DNA exhibit some mysterious features that cannot find satisfactory explanation by quantum mechanical modes of atoms. One of them, known as a Levinthal’s paradox, is the ability to preserve their complex three-dimensional structure in appropriate environments. Another one is that they possess some unknown energy mechanism. The Basic Structures of Matter Supergravitation Unified Theory (BSM-SG) allows uncovering the real physical structures of the elementary particles and their spatial arrangement in atomic nuclei. The resulting physical models of the atoms are characterized by the same interaction energies as the quantum mechanical models, while the structure of the elementary particles influence their spatial arrangement in the nuclei. The resulting atomic models with fully identifiable parameters and angular positions of the quantum orbits permit studying the physical conditions behind the structural and bonding restrictions of the atoms connected in molecules. A new method for a theoretical analysis of biomolecules is proposed. The analysis of a DNA molecule leads to formulation of hypotheses about the energy storage mechanism in DNA and its role in the cell cycle synchronization. This permits shedding a light on the DNA feature known as a C-value paradox. The analysis of a tRNA molecule leads to formulation of a hypothesis about a binary decoding mechanism behind the 20 flavors of the complex aminoacyle-tRNA synthetases - tRNA, known as a paradox.

This paper addresses methodology issues related to evidence-based healthcare research, specifically when evaluating and analyzing the hospital practice environments (HPE) impacts on the patient health outcomes are conducted in longitudinal intervention survey studies. HPE include the spatially clustered hospital characteristics, including practice environment scale (PES) measures, hospital facilities, nursing staffing and nursing attributes. The longitudinal associations between HPE and patient smoking cessation counseling (SCC) activities, and patient heart failure (HF) outcomes are examined. Various longitudinal and hierarchical modeling are compared including linear mixed models with restricted maximum likelihood estimation, generalized estimating equations with quasi-likelihood estimation, hierarchical linear regression models with nonparametric generalized least squares estimations, and repeated ANOVA. Moreover, both pre-modeling including the items/dimension reduction issues for longitudinal item-response hospital survey data and post-modeling (the mediation analysis) are discussed and conducted. Results show some methodology and solution differences when including the spatial or temporal correlations of HPE simultaneously for examining the longitudinal effects of HPE on HF core outcome measures adjusted or potentially mediated by SCC and nurse staffing environmental variables. This may have implications and potential impact for healthcare decision-making. Patients can benefit from these research findings.

Saint John has a very high rate of Sz in its mainly Irish population. In this paper I examine the possible cause of iron from cast iron piping along with iron in the diet that lead to a weakened immune system and consequent contagious disease such as Cholera. Cholera may do damage to the DNA of fertile women who pass it on to their offspring.

Here we consider the Robust Solution as applied to the cholera epidemic in Lower Canada (Quebec) in 1832. We find that the mathematics from that procedure provides the mathematical foundation or the study. The rate of growth of the virus must be kept below 14% to terminate the spread of the disease.

Advances in Genomics have re-energized interest in multiple hypothesis testing procedures but have simultaneously created new methodological and computational challenges. In Genomics for instance, it is now commonplace for experiments to measure expression levels in thousands of genes creating large multiplicity problems when thousands of hypotheses are to be tested simultaneously. Within this context we seek to identify differentially expressed genes, that is, genes whose expression levels are associated with a particular response or covariate of interest. The False Discovery Rate (FDR) is the preferred measure since the Family Wise Error Rates (FWERs) are usually overly restrictive. In the FDR methods, estimation of the proportion of null hypotheses (π0) is an important parameter that needs to be estimated.      In this paper, we compare the effectiveness of 12 methods for estimating π0 when the test statistics are continuous using simulated data with independent, weak dependence, and moderate dependence structures.

In this paper, we propose a mathematical model of turbulence flow of fluid through a deformable channel to study the pulsatile blood flow in the coronary system with arterial stenosis. Blood is assumed to be an incompressible non- Newtonian fluid and its motion is considered as turbulent and modelled by the mass and momentum conservations with turbulent mixing energy and specific dissipation rate. The mechanical deformation of the arterial wall is modelled by a hyperelastic differential equation. The pulsatile behaviour during each heartbeat is assigned on the entrance and exit boundaries. Numerical simulation based on the Finite Element method for the solution of arterial wall deformation, and the Arbitrary Lagrangian Eulerian Finite Volume method for the turbulence fluid-flow solution is used to investigate the effect of stenosis severity at the proximal part of the left anterior descending artery on the blood velocity, the pressure distribution and the wall shear stresses along the flow direction.

It is often interest of comparing two pharmacodynamics (PD) profiles in drug development. Currently the common practice is borrowing the bioequivalence (BE) rule in pharmacokinetics analysis for pharmacodynamics comparison in terms of the area under the effect curve (AUEC) of the pharmacodynamics profile. However, this may not be a feasible and sensitive enough approach since the bioequivalence approach is based on the summarized parameter of the pharmacodynamics profile rather than on directly comparison of the whole pharmacodynamics profile. In this paper, a simple but efficient and pragmatic pharmacodynamics comparability index is proposed to evaluate the comparability of pharmacodynamics profiles by comparing the whole pharmacodynamics profiles directly. Different biological products have different variability and the CV% can be in a very large range. The PD comparability index can take account of the reference knowledge into consideration in assessment but the AUEC BE type approach ignores the reference variability. The good properties of the proposed approach are illustrated through simulated data and a real dataset.

Polychotomous response models are commonly used in the clinical trials to analyze categorical or ordinal response data. Motivated by investigating of relationship between BMI categories and several risk factors, we carry out the application studies to examine the impact of risk factors on BMI categories, especially for categories of “Overweight” and “Obesities”. In this study, we apply the Bayesian methodology through a mixed-effects polychotomous response model to the Diverse Population Collaboration (DPC) dataset. Using the mixed-effects Bayesian polychotomous response model with uniform improper priors, we would get similar interpretations of the association between risk factors and BMI, which are in great agreement with the results documented in literature. Our application showed that the Bayesian mixed-effects polychotomous response model with improper priors is a very useful statistical technique for solving real word problems.

Stress is a part of human life, especially for urban citizens. Stress is inseparable characteristics of student life, especially exam days. Stress management is one of the first steps which can affect students success during the exams, especially in universities. Blood pressure is the first stress observation symptom to understand its level. Therefore, to understand the stress impact of university students during the exam weeks, a conditional experiment has been designed. 200 students were selected from Bosnian and Turkish female and male. The students` blood systolic, diastolic and heart rate were measured to detect the differences between non-exams days and exam days. The blood pressure measurement has been done 3 times in specific times, non-exam days, midterm and final days. Since non-exam days were taken as stress off days, they were supposed that these days were control data to compare with exam days to see the differences. As a result of the measurements, Bosnian females showed the highest increasing, systolic 13.2%, diastolic 9.3% and heart rate 8.5% during the midterm exam days. The group has been followed by Bosnian males, systolic 6.9%, diastolic 6.1% and heart rate 6.63 increased during the midterm days. Although Turkish students blood pressure and heart rate increased, the values were less than Bosnian students. Moreover, high correlation significance results belonged to Bosnian females and males, 0.722 and 0.698 respectively. Finally, it was concluded that if students have scholarship they have more blood pressure during the exams. While 95% of Bosnian females and 90% of Bosnian males have some scholarship, no Turkish students have scholarship demonstrated the differences between Bosnian and Turkish students blood measurements.