Kinetochore life histories reveal an Aurora-B-dependent error correction mechanism in anaphase

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Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Frequency-dependent conspecific attraction to food patches

In many ecological situations, resources are difficult to find but become more apparent to nearby searchers after one of their numbers discovers and begins to exploit them. If the discoverer cannot monopolize the resources, then others may benefit from joining the discoverer and sharing their discovery. Existing theories for this type of conspecific attraction have often used very simple rules for how the decision to join a discovered resource patch should be influenced by the number of individuals already exploiting that patch. We use a mechanistic, spatially explicit model to demonstrate that individuals should not necessarily simply join patches more often as the number of individuals exploiting the patch increases, because those patches are likely to be exhausted soon or joining them will intensify future local competition. Furthermore, we show that this decision should be sensitive to the nature of the resource patches, with individuals being more responsive to discoveries in general and more tolerant of larger numbers of existing exploiters on a patch when patches are resource-rich and challenging to locate alone. As such, we argue that this greater focus on underlying joining mechanisms suggests that conspecific attraction is a more sophisticated and flexible tactic than currently appreciated.     

Comparison of basic peptides- and lipid-based strategies for the delivery of splice correcting oligonucleotides

Expression of alternatively spliced mRNA variants at specific stages of development or in specific cells and tissues contributes to the functional diversity of the human genome. Aberrations in alternative splicing were found as a cause or a contributing factor to the development, progression, or maintenance of numerous diseases. The use of antisense oligonucleotides (ON) to modify aberrant expression patterns of alternatively spliced mRNAs is a novel means of potentially controlling such diseases. Oligonucleotides can be designed to repair genetic mutations, to modify genomic sequences in order to compensate for gene deletions, or to modify RNA processing in order to improve the effects of the underlying gene mutation. Steric block ON approach have proven to be effective in experimental model for various diseases. Here, we describe our experience in investigating two strategies for ON delivery: ON conjugation with basic peptides and lipid-based particulate system (lipoplex). Basic peptides or Cell Penetrating Peptides (CPP) such as the TAT-derived peptide appear to circumvent many problems associated with ON and drug delivery. This strategy may represent the next paradigm in our ability to modulate cell function and offers a unique avenue for the treatment of disease. Lipoplexes result from the intimate interaction of ON with cationic lipids leading to ON carrying particles able to be taken up by cells and to release ON in the cytoplasm. We have used as an experimental model the correction of a splicing alteration of the mutated β-globin intron causing thalassemia. Data on cell penetration and efficacy of correction of specific steric block ON delivered either by basic peptides or lipoplex are described. A comparison of the properties of both delivery systems is made respective to the use of this new class of therapeutic molecules.     

Determination of field output correction factors of radiophotoluminescence glass dosimeter and CC01 ionization chamber and validation against IAEA-AAPM TRS-483 code of practice

PurposeTo determine the field output correction factors of the radiophotoluminescence glass dosimeter (RPLGD) in parallel and perpendicular orientations with reference to CC01, the ionization chamber.MethodsThe dose to a small water volume and the sensitive volume of the RPLGD and the IBA-CC01 were determined for 6-MV, 100-cm SAD, 10-cm depth using egs_chamber user-code. The RPLGD in perpendicular and parallel orientations to the beam axis were studied. The field output correction factors of each detector for 0.5 × 0.5 to 10 × 10 cm² field sizes were determined. These field output correction factors were validated by comparing field output factors against data determined from IAEA-AAPM TRS-483 code of practice.ResultsThe field output correction factors of all detectors were within 5% for field sizes down to 0.8 × 0.8 cm². For 0.5 × 0.5 cm², the field output correction factors of CC01, RPLGD in perpendicular and parallel orientations differed from unity by 14%, 19%, and 5%, respectively. The percentage difference between field output factors determined using RPLGD and CC01 data, corrected using the field output correction factors determined in this work and measurements with CC01 data corrected using TRS-483, was less than 3% for all field sizes, except for the smallest field size of RPLGD in perpendicular orientation and the CC01.ConclusionsThe field output correction factors of RPLGD and CC01 are reported. The validation proves that RPLGD in parallel orientation combined with the field output correction factors is the most suitable for determining the field output factors for the smallest field used in this study.     

Studies on evolutionary and selective properties of hypercycles using a Monte Carlo method

Summary The most relevant properties of hypercycles were previously studied mainly from a theoretical point of view. We have developed a Monte Carlo method simulating hypercyclic organization to obtain information about the dynamics of this prebiotic organization. Nucleation, growth, and selective properties have been tested and the results obtained are in good agreement with those of the theoretical predictions. The influence of hypercyclic organization of the error threshold has also been studied. As a consequence of the emergence of a hypercycle, the value of this threshold decreases. The amount of this decrease depends on the population size. Moreover, for some interval of quality factor values, either the hypercycle organization or an error catastrophe can be produced, depending on the initial conditions. The influence of these phenomena on both the dynamic behavior and evolutionary advantages of the hypercycle, as well as their decisive roles on genome size, are discussed.Presented at the FEBS Symposium on Genome Organization and Evolution, held in Crete, Greece, September 1–5, 1986     

Bias of heritability estimates from twin data in presence of errors of zygosity determination

Simple heritability estimators of continuous as well as discrete traits from twin data are known to overestimate the degree of genetic determination of the measured traits for several reasons. Errors of zygosity determination will, however, underestimate the true heritability. The bias due to wrong assignment of dizygous twin pairs into monozygous type is evaluated here, and the results indicate that this negative bias has a compensatory effect on the estimate of the degree of genetic determination when other factors of similarity between twin pairs are taken into account. It is shown that when an estimate of zygosity error is available, the bias due to this factor can be evaluated quantitatively, and hence the adjustment for zygosity error can be incorporated in the estimation of the degree of genetic determination of a trait. Although this theory is explicitly developed here for twin studies, the general principle also applies for other types of errors of determining the degree of biological relationships for estimation of heritability, in which case this type of error may be more important than the simple zygosity error.     

The pentafunctional FAS1 genes of Saccharomyces cerevisiae and Yarrowia lipolytica are co-linear and considerably longer than previously estimated

Summary The fatty acid synthetase (FAS) gene FAS1 of the alkane-utilizing yeast Yarrowia lipolytica was cloned and sequenced. The gene is represented by an intron-free reading frame of 6228 by encoding a protein of 2076 amino acids and 229980 Da molecular weight. This protein exhibits a 58% sequence similarity to the corresponding Saccharomyces cerevisiae FAS -subunit. The sequential order of the five FAS1-encoded enzyme domains, acetyl transferase, enoyl reductase, dehydratase and malonyl/palmityl-transferase, is co-linear in both organisms. This finding agrees with available evidence that the functional organization of FAS genes is similar in related organisms but differs considerably between unrelated species. In addition, previously reported conflicting data concerning the 3 end of S. cerevisiae FAS1 were re-examined by genomic and cDNA sequencing of the relevant portion of the gene. Thereby, the translational stop codon was shown to lie considerably downstream of both published termination sites. The S. cerevisiae FAS1 gene thus has a corrected length of 6153 by and encodes a protein of 2051 amino acids and 228667 Da molecular weight.     

Processing of multi-dimensional NMR data with the new software PROSA

Summary The new program PROSA is an efficient implementation of the common data-processing steps for multi-dimensional NMR spectra. PROSA performs linear prediction, digital filtering, Fourier transformation, automatic phase correction, and baseline correction. High efficiency is achieved by avoiding disk storage of intermediate data and by the absence of any graphics display, which enables calculation in the batch mode and facilitates porting PROSA on a variety of different computer systems; including supercomputers. Furthermore, all time-consuming routines are completely vectorized. The elimination of a graphics display was made possible by the use of a new, reliable automatic phase-correction routine. CPU times for complete processing of a typical heteronuclear three-dimensional NMR data set of a protein vary between less than 1 min on a NEC SX3 supercomputer and 40 min on a Sun-4 computer system.     

一种复合神经元网络结构的并行动力学及快速学习算法

提出两种功能互相不同的神经细胞组成的复合神经元网络(CNN)模型;导出一种特殊结构的CNN的并行动力学;而且证明了它的稳定性。在这些结果基础上,得到快速的假逆矩阵学习算法。计算机仿真试验证实学习算法与动力学稳定性的正确性,并表现出良好的容错性能与存储容量。