Effects Of Biological Variables Research Articles

Reducing Lipid Panel Error Allowances to Improve the Accuracy of Cardiovascular Risk Stratification.

The standard lipid panel forms the backbone of atherosclerotic cardiovascular disease risk assessment. Suboptimal analytical performance, along with biological variability, could lead to erroneous risk assessment and management decisions. The current National Cholesterol Education Program (NCEP) performance recommendations have remained unchanged for almost 3 decades despite improvements in assay technology. We investigated the potential extent of risk misclassification when the current recommendations are met and explored the impact of improving analytical performance goals. We extracted lipid panel data for 8506 individuals from the NHANES database and used these to classify subjects into 4 risk groups as recommended by the 2018 US Multisociety guidelines. Analytical bias and imprecision, at the allowable limits, as well as biological variability, were introduced to the measured values to determine the impact on misclassification. Bias and imprecision were systematically reduced to determine the degree of improvement that may be achieved. Using the current performance recommendations, up to 10% of individuals were misclassified into a different risk group. Improving proportional bias by 1%, and fixing imprecision to 3% across all assays reduced misclassifications by up to 10%. The effect of biological variability can be reduced by taking the average of serial sample measurements. The current NCEP recommendations for analytical performance of lipid panel assays allow for an unacceptable degree of misclassification, leading to possible mismanagement of cardiovascular disease risk. Iteratively reducing allowable error can improve this.

J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments

BackgroundThe combined effects of biological variability and measurement-related errors on cancer sequencing data remain largely unexplored. However, the spatio-temporal simulation of multi-cellular systems provides a powerful instrument to address this issue. In particular, efficient algorithmic frameworks are needed to overcome the harsh trade-off between scalability and expressivity, so to allow one to simulate both realistic cancer evolution scenarios and the related sequencing experiments, which can then be used to benchmark downstream bioinformatics methods.ResultWe introduce a Julia package for SPAtial Cancer Evolution (J-SPACE), which allows one to model and simulate a broad set of experimental scenarios, phenomenological rules and sequencing settings.Specifically, J-SPACE simulates the spatial dynamics of cells as a continuous-time multi-type birth-death stochastic process on a arbitrary graph, employing different rules of interaction and an optimised Gillespie algorithm. The evolutionary dynamics of genomic alterations (single-nucleotide variants and indels) is simulated either under the Infinite Sites Assumption or several different substitution models, including one based on mutational signatures. After mimicking the spatial sampling of tumour cells, J-SPACE returns the related phylogenetic model, and allows one to generate synthetic reads from several Next-Generation Sequencing (NGS) platforms, via the ART read simulator. The results are finally returned in standard FASTA, FASTQ, SAM, ALN and Newick file formats.ConclusionJ-SPACE is designed to efficiently simulate the heterogeneous behaviour of a large number of cancer cells and produces a rich set of outputs. Our framework is useful to investigate the emergent spatial dynamics of cancer subpopulations, as well as to assess the impact of incomplete sampling and of experiment-specific errors. Importantly, the output of J-SPACE is designed to allow the performance assessment of downstream bioinformatics pipelines processing NGS data. J-SPACE is freely available at: https://github.com/BIMIB-DISCo/J-Space.jl.

Pediatric Pain and Neurodevelopmental Disorders: Implications for Research and Practice in Behavior Analysis.

Individuals diagnosed with a neurodevelopmental disorder also are commonly diagnosed with a medical comorbidity. Because of this, it is estimated that this population experiences nearly twice the incidence of pain or discomfort as their neurotypical peers. Although behavior analysts consider the effect of biological variables on a client's behavior, considerations of pain appear to be underdiscussed and understudied. The purpose of this article is to discuss how pain may interact with the efficacy of behavior analytic assessments and treatments, provide potential solutions to the barriers associated with pain states, and describe avenues to promote clinical research to improve our behavior analysis of pediatric pain while developing treatments for behavior problems such as aggression.

Influence of mussel biological variability on pollution biomarkers

This study deals with the identification and characterization of biological variables that may affect some of the biological responses used as pollution biomarkers. With this aim, during the 2012 mussel survey of the Spanish Marine Pollution monitoring program (SMP), at the North-Atlantic coast, several quantitative and qualitative biological variables were measured (corporal and shell indices, gonadal development and reserves composition). Studied biomarkers were antioxidant enzymatic activities (CAT, GST, GR), lipid peroxidation (LPO) and the physiological rates integrated in the SFG biomarker (CR, AE, RR). Site pollution was considered as the chemical concentration in the whole tissues of mussels.A great geographical variability was observed for the biological variables, which was mainly linked to the differences in food availability along the studied region. An inverse relationship between antioxidant enzymes and the nutritional status of the organism was evidenced, whereas LPO was positively related to nutritional status and, therefore, with higher metabolic costs, with their associated ROS generation. Mussel condition was also inversely related to CR, and therefore to SFG, suggesting that mussels keep an “ecological memory” from the habitat where they have been collected. No overall relationship was observed between pollution and biomarkers, but a significant overall effect of biological variables on both biochemical and physiological biomarkers was evidenced. It was concluded that when a wide range of certain environmental factors, as food availability, coexist in the same monitoring program, it determines a great variability in mussel populations which mask the effect of contaminants on biomarkers.

Leptin as a marker of undernutrition in breast cancer recurrence

ObjectiveTo relate leptin concentration with undernutrition and survival time in breast cancer recurrence.Design and methodsLeptin and other markers of undernutrition were measured in 49 patients who experienced disease recurrence for breast cancer. Undernutrition was clinically assessed by a weight loss of ≥10% between primary diagnosis and recurrence or ≥5% within the last month and/or the prescription of food supplements. Results were compared between patients with (21) or without (28) undernutrition by logistic regression models. The effect of biological variables on survival rate was assessed by the Kaplan‐Meier method.ResultsLeptin was significantly and negatively associated with undernutrition (OR=0.45 [0.23–0.87], p=0.018), while PINI (Prognostic Inflammatory and Nutritional Index, OR=1.24 [0.94–1.63], p=0.130) did not reach significance. The survival distributions across quartiles of leptin (Log rang test, p=0.048) and PINI (Log rank test, p=0.0001) were significantly different. However, as assessed by the Cox proportional hazards models, quartiles of leptin did not differ between each other while quartiles of PINI were all significantly different from quartile 1.ConclusionIn case of breast cancer recurrence, leptin is a good marker of undernutrition but is a poor marker of survival time, while PINI is a poor marker of undernutrition but is a good marker of survival time.

Effects of Social Stimuli on Laughing and Smiling in Young Children With Angelman Syndrome

The effects of social stimuli present and absent on laughing and smiling in 2 young children with Angelman syndrome were assessed via a multielement design. Results indicated that laughing and smiling for either child was unaffected by the social stimuli assessed in the social interaction condition. Results are discussed in terms of the effects of biological variables and environmental stimuli on children with specific genetic disorders across the lifespan.

Effect of biological variability on the robustness of NIR models for soluble solids content of apples

A statistical analysis was performed on a large spectral data set to analyse the effect of orchard, season and cultivar. Season and cultivar were responsible for a major amount of the spectral variability, whereas the influence of the orchard was low and only appeared for certain cultivars during specific seasons. The robustness of the calibration models for soluble solids content with respect to the three factors was tested based on external validations. It was found that the accuracy of the models increased considerably when including more variability in the calibration set. Further, overfitting of the calibration model was avoided. On the other hand, adding more data to the calibration set increased the chance of adding atypical data, which resulted in reduced model accuracy. It is, therefore, important to construct the calibration data set in such a way that it is representative for future measurements. When the effect of a certain factor is known a priori, e.g. cultivar, it is recommended to use specific calibration models.

Effect of biological variables and capture period on the proximate composition and fatty acid composition of the dorsal muscle tissue of Hypophthalmus edentatus (Spix, 1829)

This study analyzed the chemical composition of the dorsal muscle tissue of Hypophthalmus edentatus, in particular, fatty acids of the lipidic fraction, and its relationship with the biological variables and the capture period. The average values for moisture, ash, protein and total lipids were 63.15, 1.11, 14.27 and 17.24%, respectively. In the lipidic fraction, 35 fatty acids were identified, the most abundant being: 16:0, 18:1omega9, 18:0, 16:1omega7, 18:3omega3, DHA and EPA. The totals of respectively saturated, monounsaturated and polyunsaturated fatty acids were 41.15, 35.30 and 23.88%. The PUFA/SFA ratio was equal to 0.68 and the omega3/ omega6 ratio equal to 1.98. The PCA demonstrated that the long chain PUFAs contributed positively to the formation of the first axis. The CCA showed some effects of the biological factors (weight, reproductive cycle, sex) and the capture period on the variation of total lipids and some fatty acids.

Partition Coefficient Ratios and Tumour Perfusion Studied with 85mKr and 133Xe

The relative partition coefficients of krypton and xenon, and the regional blood flow in 27 superficial malignant tumour nodules in 22 patients with diagnosed tumours were measured using the 85mKr- and 133Xe-clearance method. In order to minimize the effect of biological variables on the measurements the radionuclides were injected simultaneously into the tumour. The distribution of the radiotracers was assumed to be in equilibrium at the beginning of the experiment. The blood perfusion was calculated by fitting a two-exponential function to the measuring points. The mean value of the perfusion rate calculated from the xenon results was 13 +/- 10 ml/(100 g.min) [range 3 to 38 ml/(100 g.min)] and from the krypton results 19 +/- 11 ml/(100 g.min) [range 5 to 45 ml/(100 g.min)]. These values were obtained, if the partition coefficients are equal to one. The equations obtained by using compartmental analysis were used for the calculation of the relative partition coefficient of krypton and xenon. The partition coefficient of krypton was found to be slightly smaller than that of xenon, which may be due to its smaller molecular weight.

The effect of biological variables on the anti-ulcerogenic effect of vegetable plantain banana.

Antiulcerogenic effect of banana have been reported from this laboratory and elsewhere but in none of these communications was the species and variety mentioned. The effects of different biological variables like size (indicating maturity), season and soil on the antiulcerogenic effect of banana have also not been reported. The data of the present study indicate that the antiulcerogenic effect of banana is present primarily in the unripe, green plantain banana obtained from plant MUSA SAPIENTUM Linn variety PARADISIACA. The antiulcerogenic principle in plantain banana appears to be present in big (mature) unripe fruits and varies from season to season and place to place in the Indian subcontinent. The antiulcerogenic principle seems to be thermolabile. Antiulcerogenic effects seems to be due to strengthening of mucosal resistance factors.