The effects of anatomical errors on shoulder kinematics computed using multi-body models

Joint motion calculated using multi-body models and inverse kinematics presents many advantages over direct marker-based calculations. However, the sensitivity of the computed kinematics is known to be partly caused by the model and could also be influenced by the participants’ anthropometry and sex. This study aimed to compare kinematics computed from an anatomical shoulder model based on medical images against a scaled-generic model and quantify the effects of anatomical errors and participants’ anthropometry on the calculated joint angles. Twelve participants have had planar shoulder movements experimentally captured in a motion lab, and their shoulder anatomy imaged using an MRI scanner. A shoulder multi-body dynamics model was developed for each participant, using both an image-based approach and a scaled-generic approach. Inverse kinematics have been performed using the two different modelling procedures and the three different experimental motions. Results have been compared using Bland–Altman analysis of agreement and further analysed using multi-linear regressions. Kinematics computed via an anatomical and a scaled-generic shoulder models differed in average from 3.2 to 5.4 degrees depending on the task. The MRI-based model presented smaller limits of agreement to direct kinematics than the scaled-generic model. Finally, the regression model predictors, including anatomical errors, sex, and BMI of the participant, explained from 41 to 80% of the kinematic variability between model types with respect to the task. This study highlighted the consequences of modelling precision, quantified the effects of anatomical errors on the shoulder kinematics, and showed that participants' anthropometry and sex could indirectly affect kinematic outcomes.

     

A germline clone screen for meiotic mutants in Drosophila melanogaster

Using an FLP/FRT-based method to create germline clones, we screened Drosophila chromosome arms 2L and 3R for new female meiotic mutants. The screen was designed to recover mutants with severe effects on meiotic exchange and/or segregation. This screen yielded 11 new mutants, including six alleles of previously known meiotic genes (c(2)M and ald/mps1). The remaining five mutants appear to define at least four new genes whose ablation results in severe meiotic defects. Three of the novel meiotic mutants were identified at the molecular level. Two of these, mcm5(A7) and trem(F9), define roles in meiotic recombination, while a third, cona(A12), is important for synaptonemal complex assembly. Surprisingly, five of the nine mutants for which the lesion has been identified at the molecular level are not the result of mutations characteristic of EMS mutagenesis, but rather due to the insertion of the transposable element Doc. This study demonstrates the utility of germline clone-based screens for the discovery of strong meiotic mutants, including mutations in essential genes, and the use of molecular genetic techniques to map the loci.     

Identification and functional characterization of three chicken cathelicidins with potent antimicrobial activity

Cathelicidins comprise a family of antimicrobial peptides sharing a highly conserved cathelin domain. Here we report that the entire chicken genome encodes three cathelicidins, namely fowlicidin-1 to -3, which are densely clustered within a 7.5-kb distance at the proximal end of chromosome 2p. Each fowlicidin gene adopts a fourexon, three-intron structure, typical for a mammalian cathelicidin. Phylogenetic analysis revealed that fowlicidins and a group of distantly related mammalian cathelicidins known as neutrophilic granule proteins are likely to originate from a common ancestral gene prior to the separation of birds from mammals, whereas other classic mammalian cathelicidins may have been duplicated from the primordial gene for neutrophilic granule proteins after mammals and birds are diverged. Similar to ovine cathelicidin SMAP-29, putatively mature fowlicidins displayed potent and salt-independent activities against a range of Gram-negative and Gram-positive bacteria, including antibiotic-resistant strains, with minimum inhibitory concentrations in the range of 0.4-2.0 microm for most strains. Fowlicidin-1 and -2 also showed cytotoxicity, with 50% killing of mammalian erythrocytes or epithelial cells in the range of 6-40 microm. In addition, two fowlicidins demonstrated a strong positive cooperativity in binding lipopolysaccharide (LPS), resulting in nearly complete blockage of LPS-mediated proinflammatory gene expression in RAW264.7 cells. Taken together, fowlicidin-1 and -2 are clearly among the most potent cathelicidins that have been reported. Their broad spectrum and salt-insensitive antibacterial activities, coupled with their potent LPS-neutralizing activity, make fowlicidins excellent candidates for novel antimicrobial and anti-sepsis agents.     

Hypoxia Transiently Sequesters Mps1 and Polo to Collagenase-Sensitive Filaments in Drosophila Prometaphase Oocytes

Background

The protein kinases Mps1 and Polo, which are required for proper cell cycle regulation in meiosis and mitosis, localize to numerous ooplasmic filaments during prometaphase in Drosophila oocytes. These filaments first appear throughout the oocyte at the end of prophase and are disassembled after egg activation.

Methodology/Principal Findings

We showed here that Mps1 and Polo proteins undergo dynamic and reversible localization to static ooplasmic filaments as part of an oocyte-specific response to hypoxia. The observation that Mps1- and Polo-associated filaments reappear in the same locations through multiple cycles of oxygen deprivation demonstrates that underlying structural components of the filaments must still be present during normoxic conditions. Using immuno-electron microscopy, we observed triple-helical binding of Mps1 to numerous electron-dense filaments, with the gold label wrapped around the outside of the filaments like a garland. In addition, we showed that in live oocytes the relocalization of Mps1 and Polo to filaments is sensitive to injection of collagenase, suggesting that the structural components of the filaments are composed of collagen-like fibrils. However, the collagen-like genes we have been able to test so far (vkg and CG42453) did not appear to be associated with the filaments, demonstrating that the collagenase-sensitive component of the filaments is one of a number of other Drosophila proteins bearing a collagenase cleavage site. Finally, as hypoxia is known to cause Mps1 protein to accumulate at kinetochores in syncytial embryos, we also show that GFP-Polo accumulates at both kinetochores and centrosomes in hypoxic syncytial embryos.

Conclusions/Significance

These findings identify both a novel cellular structure (the ooplasmic filaments) as well as a new localization pattern for Mps1 and Polo and demonstrate that hypoxia affects Polo localization in Drosophila.     

Statistical Analysis of Nondisjunction Assays in Drosophila

Many advances in the understanding of meiosis have been made by measuring how often errors in chromosome segregation occur. This process of nondisjunction can be studied by counting experimental progeny, but direct measurement of nondisjunction rates is complicated by not all classes of nondisjunctional progeny being viable. For X chromosome nondisjunction in Drosophila female meiosis, all of the normal progeny survive, while nondisjunctional eggs produce viable progeny only if fertilized by sperm that carry the appropriate sex chromosome. The rate of nondisjunction has traditionally been estimated by assuming a binomial process and doubling the number of observed nondisjunctional progeny, to account for the inviable classes. However, the correct way to derive statistics (such as confidence intervals or hypothesis testing) by this approach is far from clear. Instead, we use the multinomial-Poisson hierarchy model and demonstrate that the old estimator is in fact the maximum-likelihood estimator (MLE). Under more general assumptions, we derive asymptotic normality of this estimator and construct confidence interval and hypothesis testing formulae. Confidence intervals under this framework are always larger than under the binomial framework, and application to published data shows that use of the multinomial approach can avoid an apparent type 1 error made by use of the binomial assumption. The current study provides guidance for researchers designing genetic experiments on nondisjunction and improves several methods for the analysis of genetic data.MEIOSIS is a specialized cell division, where a diploid cell undergoes a single round of replication followed by two rounds of segregation to produce four haploid gametes. During this segregation, chromosomes must correctly separate (or disjoin) from their homologs at meiosis I, followed by sister chromatids disjoining at meiosis II. When chromosomes fail to disjoin from their partners, the resultant nondisjunction produces aneuploid gametes with the wrong number of chromosomes. The study of meiotic nondisjunction in Drosophila has a long and distinguished history of publication in genetics, with the inaugural article published in this journal being Calvin Bridges'' use of nondisjunction to prove the chromosome theory of heredity (Bridges 1916). The first study that screened variants isolated from natural populations used nondisjunction to identify meiotic mutants (Sandler et al. 1968), as did the first EMS-induced mutant screen (Baker and Carpenter 1972). Subsequent screens using new mutagens or techniques have also relied on measuring nondisjunction to identify mutants of interest (Sekelsky et al. 1999). Indeed, much of the progress that has been made in the study of meiosis would not have been possible without the use of nondisjunction to identify new mutations that are defective at some step in chromosome segregation.However, one difficulty in estimating nondisjunction rates is that in most instances the resulting aneuploid progeny cannot survive. Fortunately, in Drosophila it is possible to design crosses to recover them. Sex determination in flies is based on the number of X chromosomes, rather than a masculinizing Y chromosome as in mammals. This means that XO flies are viable (but sterile) males, while XXY flies are viable females. Therefore, it is possible to recover both normal and nondisjunctional progeny, as a nullo-X egg fertilized by an X-bearing sperm will survive as an XO male, while a diplo-X egg fertilized by a sperm lacking an X will be female (XXY). By using visible markers on the sex chromosomes, these exceptional progeny are straightforward to identify. However, if those eggs are fertilized by the other class of sperm, the resulting OY or XXX progeny are inviable. Therefore, the nondisjunction rate that occurs during meiosis is not equal to the proportion of nondisjunctional progeny, as only 50% of nondisjunctional eggs receive sperm compatible with viability, while all normal eggs are viable.Given this experimental limitation, what is the correct method to calculate the error rate during meiosis? For this discussion, let N be the total number of progeny produced in an experiment, let X₁ be the number of inviable nondisjunctional progeny (OY and XXX), let X₂ be the number of viable nondisjunctional progeny (XO and XXY), and let X₃ be the number of normal progeny (XY and XX), such that N = X₁ + X₂ + X₃. If all progeny could be counted, then the nondisjunction rate would simply be (X₁ + X₂)/N.However, only flies that survive to adulthood can be counted, and therefore both X₁ and N are unknown. As X- and Y-bearing sperm are produced in equal numbers, live and dead nondisjunctional progeny are also expected in equal numbers. Therefore, K.W. Cooper (Cooper 1948) proposed the widely used estimator for the X chromosome nondisjunction rate, where X₂ is substituted for X₁ in the above formula, giving the rate as:(1)While this estimator works, the statistical properties of this estimator are not clear. Instead of following the early literature to combine X₁ and X₂ and use a binomial distribution, we go back to the three original categories and model the process as a multinomial distribution with latent number of progeny N, considering all three possible phenotypes for each progeny (nondisjunctional dead, nondisjunctional living, and normal). Whether a nondisjunctional oocyte becomes a nondisjunctional dead or nondisjunctional living progeny depends on the sex chromosome content of the sperm that fertilized it. As X- and Y-bearing sperm are produced in equal numbers during male meiosis, the usual genetic expectation for the rates of nondisjunctional dead and living progeny will be . However, even assuming that the rates of nondisjunctional dead and living progeny are different, with a Poisson assumption of N, we can derive the maximum-likelihood estimators (MLEs) for the nondisjunctional dead and nondisjunctional living rates. Under the usual genetic expectation of equality, the MLE of the nondisjunctional rate coincides with Cooper''s estimator, and we furthermore derive the exact distribution of . Under another set of reasonable assumptions, we show the consistency and asymptotic normality of Cooper''s estimator, and derive asymptotic results when comparing two nondisjunction rates. All these distributional results enable us to develop confidence interval and hypothesis testing related to p, or p_x − p_y in the case of comparing two nondisjunction rates from populations x and y.     

Pesticide exposure: the hormonal function of the female reproductive system disrupted?

Some pesticides may interfere with the female hormonal function, which may lead to negative effects on the reproductive system through disruption of the hormonal balance necessary for proper functioning. Previous studies primarily focused on interference with the estrogen and/or androgen receptor, but the hormonal function may be disrupted in many more ways through pesticide exposure. The aim of this review is to give an overview of the various ways in which pesticides may disrupt the hormonal function of the female reproductive system and in particular the ovarian cycle. Disruption can occur in all stages of hormonal regulation: 1. hormone synthesis; 2. hormone release and storage; 3. hormone transport and clearance; 4. hormone receptor recognition and binding; 5. hormone postreceptor activation; 6. the thyroid function; and 7. the central nervous system. These mechanisms are described for effects of pesticide exposure in vitro and on experimental animals in vivo. For the latter, potential effects of endocrine disrupting pesticides on the female reproductive system, i.e. modulation of hormone concentrations, ovarian cycle irregularities, and impaired fertility, are also reviewed. In epidemiological studies, exposure to pesticides has been associated with menstrual cycle disturbances, reduced fertility, prolonged time-to-pregnancy, spontaneous abortion, stillbirths, and developmental defects, which may or may not be due to disruption of the female hormonal function. Because pesticides comprise a large number of distinct substances with dissimilar structures and diverse toxicity, it is most likely that several of the above-mentioned mechanisms are involved in the pathophysiological pathways explaining the role of pesticide exposure in ovarian cycle disturbances, ultimately leading to fertility problems and other reproductive effects. In future research, information on the ways in which pesticides may disrupt the hormonal function as described in this review, can be used to generate specific hypotheses for studies on the effects of pesticides on the ovarian cycle, both in toxicological and epidemiological settings.     

Comprehensive evaluation of isoprenoid biosynthesis regulation in Saccharomyces cerevisiae utilizing the Genome Reporter Matrix

Gene expression profiling is rapidly becoming a mainstay of functional genomic studies. However, there have been relatively few studies of how the data from expression profiles integrate with more classic approaches to examine gene expression. This study used gene expression profiling of a portion of the genome of Saccharomyces cerevisiae to explore the impact of blocks in the isoprenoid biosynthetic pathway on the expression of genes and the regulation of this pathway. Approximately 50% of the genes whose expression was altered by blocks in isoprenoid biosynthesis were genes previously known to participate in the pathway. In contrast to this simple correspondence, the regulatory patterns revealed by different blocks, and in particular by antifungal azoles, was complex in a manner not anticipated by earlier studies.     

Crystal structure of the YgfZ protein from Escherichia coli suggests a folate-dependent regulatory role in one-carbon metabolism

The ygfZ gene product of Escherichia coli represents a large protein family conserved in bacteria to eukaryotes. The members of this family are uncharacterized proteins with marginal sequence similarity to the T-protein (aminomethyltransferase) of the glycine cleavage system. To assist with the functional assignment of the YgfZ family, the crystal structure of the E. coli protein was determined by multiwavelength anomalous diffraction. The protein molecule has a three-domain architecture with a central hydrophobic channel. The structure is very similar to that of bacterial dimethylglycine oxidase, an enzyme of the glycine betaine pathway and a homolog of the T-protein. Based on structural superposition, a folate-binding site was identified in the central channel of YgfZ, and the ability of YgfZ to bind folate derivatives was confirmed experimentally. However, in contrast to dimethylglycine oxidase and T-protein, the YgfZ family lacks amino acid conservation at the folate site, which implies that YgfZ is not an aminomethyltransferase but is likely a folate-dependent regulatory protein involved in one-carbon metabolism.