Non-equilibrium allele frequency spectra via spectral methods

A major challenge in the analysis of population genomics data consists of isolating signatures of natural selection from background noise caused by random drift and gene flow. Analyses of massive amounts of data from many related populations require high-performance algorithms to determine the likelihood of different demographic scenarios that could have shaped the observed neutral single nucleotide polymorphism (SNP) allele frequency spectrum. In many areas of applied mathematics, Fourier Transforms and Spectral Methods are firmly established tools to analyze spectra of signals and model their dynamics as solutions of certain Partial Differential Equations (PDEs). When spectral methods are applicable, they have excellent error properties and are the fastest possible in high dimension; see Press et al. (2007). In this paper we present an explicit numerical solution, using spectral methods, to the forward Kolmogorov equations for a Wright–Fisher process with migration of K populations, influx of mutations, and multiple population splitting events.     

An alternative method for assessing early mortality in contemporary populations

Biological anthropologists are interested in a population's early mortality rates for a variety of reasons. Early mortality (infant or juvenile) is of obvious importance to those interested in demography, but early mortality statistics are useful for life history analysis, paleodemography, and human adaptability studies, among others. In general, the form of mortality statistics is derived from demography, where chronological age is the gold standard for statistical calculation and comparison. However, there are numerous problems associated with the collection, analysis, and interpretation of early mortality statistics based on age, particularly for anthropological research, which is often conducted in small or non-calendrical-age numerate populations. The infant mortality rate (IMR), for example, is notoriously difficult to determine in populations where accurate accounting of age is not routine, and yet it is widely used in demography, public health, medicine, and social science research. Here we offer an alternative to age-based early mortality statistics that makes use of human biologists' interest in, and skill at, assessing human growth and development. Our proposal is to use developmental stages of juveniles instead of relying exclusively on age as the basis for mortality statistics. Death or survival according to a developmental stage (such as crawling or weaning) may provide more accurate data that are also more closely related to the cause of death. Developmental stages have the added advantage of putting infants and children back at the center of the discussion of early mortality by focusing on their activities in relation to their environment. A case study from the Turkana population of Kenya illustrates the use of developmental stages in describing early mortality. Am J Phys Anthropol 107:315–330, 1998. © 1998 Wiley-Liss, Inc.     

Protective effects of MLIF analogs on cerebral ischemia-reperfusion injury in rats

The monocyte locomotion inhibitory factor (MLIF) is an anti-inflammatory oligopeptide produced by Entamoeba histolytica. Among its different effects, it inhibits locomotion of human monocytes, hence its original name. The carboxyl-terminal end group Cys-Asn-Ser is the pharmacophore of anti-inflammatory peptide Met-Gln-Cys-Asn-Ser. In this study, the N-terminal of Cys-Asn-Ser was modified. With the aim to enhance the antioxidant ability and penetrability of Cys-Asn-Ser, we designed and synthesized two tetrapeptides Tyr-Cys-Asn-Ser and His-Cys-Asn-Ser. The neuroprotective effects of Tyr-Cys-Asn-Ser and His-Cys-Asn-Ser on focal ischemia reperfusion were investigated, and their pharmacological activities compared with Cys-Asn-Ser were studied. In order to study the mechanism of neuroprotective effect of these peptides, the level of oxidative stress markers malondialdehyde (MDA) and superoxide dismutase (SOD) and pro-inflammatory factors interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and myeloperoxidase (MPO) were detected in brain tissue homogenate.     

Bayesian survival analysis using a MARS model

A Bayesian multivariate adaptive regression spline fitting approach is used to model univariate and multivariate survival data with censoring. The possible models contain the proportional hazards model as a subclass and automatically detect departures from this. A reversible jump Markov chain Monte Carlo algorithm is described to obtain the estimate of the hazard function as well as the survival curve.     

Comparison of Different Standard Methods to Evaluate the Total Concentrations of Heavy Metals in Waste Rock

The mining industry is a very rapidly increasing production sector in Finland. Many new mines have been opened recently and others are in the planning phase. Mining legislation has been recently revised and compilation of an ID-directive (Industrial Emission Directive, 2010) required to implement environmental law revision is in progress. The aim of this study was to compare different digestion methods recommended by the Finnish Environmental Administration for threshold and guideline value determinations in the Finnish PIMA Decree (214/2007) and Government Decree (591/2006) concerning recovery of certain wastes in earth construction. Altogether six methods were tested, of which five were microwave-assisted acid digestion methods: ISO 11466, EPA Method 3051A (aqua region), EPA Method 3051A (HNO₃), EPA Method 3051A (HNO₃/HCl), and SFS-EN 13656, while one was a fusion method with lithium tetraborate (ASTM C 1391 - 95). The results showed that concentrations of heavy metals (As, Cd, Co, Cu, Ni, Pb, Sb, V, and Zn) can be determined reproducibly with standard methods, but the chemical method used can have a significant impact on the results. This conclusion is very important, because the measured heavy metal values can affect the classification and processing of waste materials, and thereby can significantly impact the cost of treatment.     

Review of Glycosylation Engineering of Biopharmaceuticals: Methods and Protocols

The glycoform profile of a glycoprotein is non-templated, i.e., is not encoded within the genome or otherwise predetermined; however, it is estimated that ~50% of human genes having an open reading frame encode a –N-X-S/T- amino acid sequence, where X represents any amino acid other than proline, that comprises a potential site (sequon) for N-linked glycosylation of the translated protein. N-linked glycosylation is both a co- and post-translational modification. The complex oligosaccharide GlcNAc2Man9Glu3 may be added at a –N-X-S/T- sequon as the polypeptide chain emerges from the ribosome tunnel. Local secondary structure determines whether oligosaccharide is added and the extent of addition. Higher occupancy is observed for –N-X-T- sequons than at –N-X-S- sequons, and the efficiency of addition can be further influenced by adjacent amino acid residues.     

Role of p53/FAK association and p53 phosphorylation in staurosporine-mediated apoptosis: Wild type versus mutant p53-R175H

A novel survival role of focal adhesion kinase (FAK) that involves its nuclear translocation and direct association with p53 has been demonstrated. Here we examined the relationship between the p53/FAK interaction and Ser46 phosphorylation of p53 (p-p53^Ser46) in the apoptotic regulation of human esophageal squamous cell carcinoma (HOSCC) cell lines, expressing either wild type (wt) p53 or mutant (mt) p53-R175H. In contrast to the wt p53 cell lines, the mt p53-R175H cell line was resistant to staurosporine (STS)-mediated detachment and caspase-3 activation. Furthermore, despite the resistance of mt p53-R175H to Ser46 phosphorylation, both wt and mt HOSCC cells translocate FAK into the nucleus and maintain the p53/FAK interaction post STS treatment. These findings provide unique insight into how tumor cells harboring the R175H mutant may resist chemotherapeutic intervention.

Structured summary

MINT-7294020: FAK (uniprotkb:Q05397) physically interacts (MI:0915) with p53 (uniprotkb:P04637) by anti-bait coimmunoprecipitation (MI:0006)     

Estimating infection prevalence: Best practices and their theoretical underpinnings

Accurately estimating infection prevalence is fundamental to the study of population health, disease dynamics, and infection risk factors. Prevalence is estimated as the proportion of infected individuals (“individual‐based estimation”), but is also estimated as the proportion of samples in which evidence of infection is detected (“anonymous estimation”). The latter method is often used when researchers lack information on individual host identity, which can occur during noninvasive sampling of wild populations or when the individual that produced a fecal sample is unknown. The goal of this study was to investigate biases in individual‐based versus anonymous prevalence estimation theoretically and to test whether mathematically derived predictions are evident in a comparative dataset of gastrointestinal helminth infections in nonhuman primates. Using a mathematical model, we predict that anonymous estimates of prevalence will be lower than individual‐based estimates when (a) samples from infected individuals do not always contain evidence of infection and/or (b) when false negatives occur. The mathematical model further predicts that no difference in bias should exist between anonymous estimation and individual‐based estimation when one sample is collected from each individual. Using data on helminth parasites of primates, we find that anonymous estimates of prevalence are significantly and substantially (12.17%) lower than individual‐based estimates of prevalence. We also observed that individual‐based estimates of prevalence from studies employing single sampling are on average 6.4% higher than anonymous estimates, suggesting a bias toward sampling infected individuals. We recommend that researchers use individual‐based study designs with repeated sampling of individuals to obtain the most accurate estimate of infection prevalence. Moreover, to ensure accurate interpretation of their results and to allow for prevalence estimates to be compared among studies, it is essential that authors explicitly describe their sampling designs and prevalence calculations in publications.