Stability of hematological analytes during 48 hours storage at three temperatures using Cell-Dyn hematology analyzer

BackgroundThe complete blood count (CBC) with differential leukocyte count (DLC) is one of the most common tests requested by physicians. The results of this test are affected by storage temperature and time of incubation. This study was designed to evaluate the stability of hematologic parameters in blood specimens stored for 48 h at three temperatures.MethodsK2-EDTA - blood was collected from 22 healthy adults. The CBC was performed using a hematology analyser immediately; 0 time point and at 4, 8, 12, 16, 20, 24, and 48 h after storage at 4 °C, 10 °C or 23 °C. Changes in values of CBC parameters from the 0 time point were determined and reported as % of the initial value.ResultsRed blood cells, platelet, hemoglobin, and mean corpuscular hemoglobin were found stable during 48 h storage at 4 °C, 10 °C or 23 °C. Hematocrite and mean corpuscular volume increased, while white blood cells decreased at 48 h when stored at 23 °C. Lymphocytes, neutrophils, eosinophils, and basophils showed significant differences after 12 h of storage at 23 °C.ConclusionsRed blood cells, platelet, hemoglobin, and mean corpuscular hemoglobin are the only suitable parameters without refrigeration during 24 h storage. When CBC and DLC are performed, 4 °C can be recommended as the most suitable storage temperature for 12 h storage.     

Distinguishing dung from blue, red and yellow-backed duikers through noninvasive genetic techniques

Dung counts have been widely used to estimate duiker abundance and densities in tropical African forests. However, one of the major limitations of this method is that species' identification of dung based on morphological characteristics is extremely difficult in most cases. Some authors made the assumption that dung pellets could at least be distinguishable between the blue duiker, the red duikers and the yellow-backed duiker. However, this study is the first attempt to test the reliability of field identification. In this study, we suggest a method based on a noninvasive genetic protocol to identify duiker species. The comparison of field and genetic identifications shows that only dung from Cephalophus silvicultor was identified in the field without error. The rate of error for red duikers and the blue duiker is high and any attempt to distinguish among those species will result in wrong estimations for each species. We recommend the use of DNA tests to ensure reliable species' identification when duiker censuses based on dung counts are used. This methodological input will probably strengthen the dung count technique and increase its reliability for duiker species abundance estimations and spatial distribution studies.     

LRP1B mutation is associated with tumor HPV status and promotes poor disease outcomes with a higher mutation count in HPV-related cervical carcinoma and head & neck squamous cell carcinoma

Human papillomavirus (HPV) infection and gene mutations were reputed as key factors in cervical carcinoma (CC) and head and neck squamous cell carcinoma (HNSCC). However, the associations of HPV status and gene mutations remain to be determined. This study aims to identify molecular patterns of LRP1B mutation and HPV status via rewiring tumor samples of HNSCC (n=1478) and CC (n=178) from the TCGA dataset. Here, we found that LRP1B mutation was associated with HPV status in CC (P=0.040) and HNSCC (P=0.044), especially in HPV 16 integrated CC (P=0.036). Cancer survival analysis demonstrated that samples with LRP1B mutation showed poor disease outcomes in CC (P=0.013) and HNSCC (P=0.0124). In addition, the expression status of LPR1B was more favorable for prediction than TP53 or RB1 in CC and HNSCC. Mutation clustering analysis showed that samples with LRP1B mutation showed higher mutation count in CC (P=1.76e-67) and HNSCC (P<10e-10). Further analysis identified 289 co-occurrence genes in these two cancer types, which were enriched in PI3K signaling, cell division process, and chromosome segregation process, et al. The 289-co-occurrence gene signature identified a cluster of patients with a higher portion of copy number variation (CNV) lost in the genome, different tumor HPV status (P<10e-10), higher mutation count (P<10e-10), higher fraction genome altered value (P=2.078e-4), higher aneuploidy score (P=3.362e-4), and earlier started the smoking year (P=2.572e-4), which were associated with shorter overall survival (P=0.0103) in CC and HNSCC samples. Overall, LRP1B mutation was associated with tumor HPV status and was an unfavorable prognostic biomarker for CC and HNSCC.     

Estimation and comparison of flowering curves

Background: Many researchers have simply recorded first flowering dates, while others have recorded the full extent of flowering. Such flowering curves show the rate of increase and decrease in flowering, as well as the day on which flowering is a maximum.

Aim: To develop objective statistical methods for the estimation and comparison of flowering curves, with particular emphasis on the date of maximal flowering.

Methods: We considered data collected either as percentages or as actual counts of numbers of flowers. We developed appropriate techniques for fitting regression curves involving non-linear least squares and Poisson regression, including a new generalisation of the epsilon-skew-normal curve.

Results: Our generalised regression curve was found to be sufficiently flexible to provide good estimates of flowering in a wide variety of situations. The five parameters of this curve have a direct and straightforward interpretation, namely the date and magnitude of maximum flowering, along with the spread, skewness and kurtosis of flowering. The method of maximum likelihood was used to provide estimates and confidence limits for the parameters and to compare Crocosmia flowering curves over eight consecutive years.

Conclusions: Regression curves, particularly those of the generalised skew-normal, give an effective, practical and objective procedure for estimating and comparing flower curves.     

A new mixed‐effects regression model for the analysis of zero‐modified hierarchical count data

Count data sets are traditionally analyzed using the ordinary Poisson distribution. However, such a model has its applicability limited as it can be somewhat restrictive to handle specific data structures. In this case, it arises the need for obtaining alternative models that accommodate, for example, (a) zero‐modification (inflation or deflation at the frequency of zeros), (b) overdispersion, and (c) individual heterogeneity arising from clustering or repeated (correlated) measurements made on the same subject. Cases (a)–(b) and (b)–(c) are often treated together in the statistical literature with several practical applications, but models supporting all at once are less common. Hence, this paper's primary goal was to jointly address these issues by deriving a mixed‐effects regression model based on the hurdle version of the Poisson–Lindley distribution. In this framework, the zero‐modification is incorporated by assuming that a binary probability model determines which outcomes are zero‐valued, and a zero‐truncated process is responsible for generating positive observations. Approximate posterior inferences for the model parameters were obtained from a fully Bayesian approach based on the Adaptive Metropolis algorithm. Intensive Monte Carlo simulation studies were performed to assess the empirical properties of the Bayesian estimators. The proposed model was considered for the analysis of a real data set, and its competitiveness regarding some well‐established mixed‐effects models for count data was evaluated. A sensitivity analysis to detect observations that may impact parameter estimates was performed based on standard divergence measures. The Bayesian ‐value and the randomized quantile residuals were considered for model diagnostics.     

Nonparametric scanning tests of homogeneity for hierarchical models with continuous covariates

In many applications of hierarchical models, there is often interest in evaluating the inherent heterogeneity in view of observed data. When the underlying hypothesis involves parameters resting on the boundary of their support space such as variances and mixture proportions, it is a usual practice to entertain testing procedures that rely on common heterogeneity assumptions. Such procedures, albeit omnibus for general alternatives, may entail a substantial loss of power for specific alternatives such as heterogeneity varying with covariates. We introduce a novel and flexible approach that uses covariate information to improve the power to detect heterogeneity, without imposing unnecessary restrictions. With continuous covariates, the approach does not impose a regression model relating heterogeneity parameters to covariates or rely on arbitrary discretizations. Instead, a scanning approach requiring continuous dichotomizations of the covariates is proposed. Empirical processes resulting from these dichotomizations are then used to construct the test statistics, with limiting null distributions shown to be functionals of tight random processes. We illustrate our proposals and results on a popular class of two-component mixture models, followed by simulation studies and applications to two real datasets in cancer and caries research.     

High prevalence of vitamin D deficiency in HIV-infected individuals in comparison with the general population across Punjab province,Pakistan

The status of vitamin D in individuals infected with human immunodeficiency virus (HIV), particularly in naïve as well as treated patients, has never been reported in the Pakistani population. A cross-sectional study was performed to measure vitamin D in individuals infected with HIV living in various districts of the Punjab, Pakistan. 1000 persons attending various treatment centers of the Punjab were screened for HIV, hepatitis B virus (HBV), hepatitis C virus (HCV), and Syphilis. Total 398 patients met inclusion criteria and vitamin D level was measured in respective cases by using enzyme-linked immunosorbent assay (ELISA) technique. 232 samples from the healthy population were also included in present research. Demographic history and clinical parameters regarding HIV disease were evaluated. Comparison of variables was done to find out the link between vitamin D levels and characteristics of HIV infected persons and comparison to that of healthy individuals was performed. Among 398 HIV patients vitamin D deficiency and insufficiency was found among 15 % and 39 % while majority of the control participants had sufficient levels of vitamin D (78 %). Most of the HIV infected individuals were males (68.6 %) and had age between 24 and 47 years (67.8 %). A significant relationship was found for vitamin D level, lifestyle and CD4 count among HIV + ve non acquired immunodeficiency syndrome (AIDS) subjects (95 % CI; p < 0.001, p = 0.09). For HIV + ve AIDS patients vitamin D had a significant relationship with lifestyle along with HIV viral load and CD4 count. Hypovitaminosis D prevails among the HIV infected population of Punjab, Pakistan.     

Microbiological study of khoa sold in Chambal region (Madhya Pradesh): A case study

Present study was conducted to analyze bacterial contaminants /pathogens in Khoa samples sold in Chambal region of Madhya Pradesh. Total Fifty samples of Khoa were brought from different localities of Chambal region at random and processed. Bacterial colony counts were also performed. Staphylococcus species and Streptococcus species were the predominant isolates. The viable counts obtained ranged from 1.3sX10⁴ to 2.1sX10⁶ CFU/g. Contamination of Khoa by pathogenic bacteria could be an important factor of gastrointestinal infections including food poisoning and food borne illness. Adequate consumer protection can be achieved by measuring the microbiological data of product.     

Isolation from a marching band increases haemocyte density in wild locusts (Chortoicetes terminifera)

1. The density‐dependent prophylaxis hypothesis predicts that individuals in high‐density populations will invest more resources in immune defence than individuals at lower densities. 2. However, recent work suggests that this prediction may not apply to all situations; solitarious species may paradoxically have higher scores than crowded counterparts in certain immune assays. 3. To investigate the relationship between a key immune parameter and field population densities, the total haemocyte counts (THCs) of Australian plague locusts (Chortoicetes terminifera) from three population densities in Western Australia were compared. 4. THCs were negatively correlated with field population densities, and locusts removed from a marching band and kept in isolation had increased THCs relative to group‐housed controls. 5. These results demonstrate that immune investment can inversely relate to population density in field conditions. 6. We suggest that isolated locusts increase their haemocyte densities relative to crowded conspecifics in response to potentially greater exposure to parasitoids and nematodes.     

A nonparametric method of estimation of the population size in capture–recapture experiments

A recent method for estimating a lower bound of the population size in capture–recapture samples is studied. Specifically, some asymptotic properties, such as strong consistency and asymptotic normality, are provided. The introduced estimator is based on the empirical probability generating function (pgf) of the observed data, and it is consistent for count distributions having a log-convex pgf (-class). This is a large family that includes mixed and compound Poisson distributions, and their independent sums and finite mixtures as well. The finite-sample performance of the lower bound estimator is assessed via simulation showing a better behavior than some close competitors. Several examples of application are also analyzed and discussed.