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PubMed1994

Pharmacological and non-pharmacological smoking motives: a replication and extension.

Cigarette smokers (n = 387) completed a questionnaire measure of smoking motives, and subgroups of this sample provided external validation information. Seven factors emerged from a principal components' analysis: automatic, sedative, addictive, stimulation, psychosocial, indulgent and sensorimotor manipulation. A higher-order principal components analysis revealed the presence of two second-order factors. Inspection of the pattern of correlations between factor scores and criterion variables clearly indicated that the first four factors above and their underlying second-order factor are more closely related to nicotine pharmacology and mood-altering effects of nicotine than the latter three motives and their underlying second-order factor. Moreover, the positive correlations between these pharmacological motives and age, coupled with a negative relationship between age and the non-pharmacological motives, support the description of the smoking career as a progressive transfer of reward from non-pharmacological to pharmacological factors. These findings suggest that self-reported reasons for smoking represent more than bias in verbal report.

Adult↗
PubMed2004

The Coach-Athlete Relationship Questionnaire (CART-Q): development and initial validation.

The purpose of the present study was to develop and validate a self-report instrument that measures the nature of the coach-athlete relationship. Jowett et al.'s (Jowett & Meek, 2000; Jowett, in press) qualitative case studies and relevant literature were used to generate items for an instrument that measures affective, cognitive, and behavioral aspects of the coach-athlete relationship. Two studies were carried out in an attempt to assess content, predictive, and construct validity, as well as internal consistency, of the Coach-Athlete Relationship Questionnaire (CART-Q), using two independent British samples. Principal component analysis and confirmatory factor analysis were used to reduce the number of items, identify principal components, and confirm the latent structure of the CART-Q. Results supported the multidimensional nature of the coach-athlete relationship. The latent structure of the CART-Q was underlined by the latent variables of coaches' and athletes' Closeness (emotions), Commitment (cognitions), and Complementarity (behaviors).

Factor Analysis, Statistical↗
PubMed2000

Characterization of natural illuminants in forests and the use of digital video data to reconstruct illuminant spectra.

We describe illumination spectra in forests and show that they can be accurately recovered from recorded digital video images. Natural illuminant spectra of 238 samples measured in temperate forests were characterized by principal-component analysis. The spectra can be accurately approximated by the mean and the first two principal components. Compared with illumination under open skies, the loci of forest illuminants are displaced toward the green region in the chromaticity plots, and unlike open sky illumination they cannot be characterized by correlated color temperature. We show that it is possible to recover illuminant spectra accurately from digital video images by a linear least-squares-fit estimation technique. The use of digital video data in spectral analysis provides a promising new approach to the studies of the spatial and temporal variation of illumination in natural scenes and the understanding of color vision in natural environments.

Color↗
PubMed2000

Obstructive sleep apnea (OSA): a cephalometric analysis of severe and non-severe OSA patients. Part II: A predictive discriminant function analysis.

One hundred male obstructive sleep apnea (OSA) patients were classified into 2 groups on the basis of apnea-hypopnea index (AHI) as severe (AHI > or = 50) and non-severe (AHI < 50). A comprehensive cephalometric analysis of cervicocraniofacial skeletal and upper airway soft tissue morphology was performed in 51 non-severe and 49 severe OSA patients. In addition, a multivariate statistical method (principal component, analysis and predictive discriminant analysis) was performed to identify the components that could correctly differentiate the severe from the non-severe OSA patients. Eight principal components (PCs) of cervicocraniofacial skeletal morphology, 4 PCs of hyoid bone position and head posture, and 7 PCs of upper airway soft tissue morphology, together with the selected demographic variables, were deduced to formulate a linear canonical discriminant function. The equation of a 9-variable model was generated as follows: PDF score = 4.127 - 0.144 (Body Mass Index) - 0.376 (PC1.1) + 0.311 (PC1.4) + 0.214 (PC1.5) + 0.075 (PC 2.1) - 1.309 (PC2.3) + 0.708 (PC3.2) - 0.059 (PC3.3) + 0.609 (PC3.6). The cutoff score was -0.03899. The overall rate of correct classification was 83%. The results showed that Body Mass Index and 8 other PCs contributed significantly to the OSA severity. These analyses are proven to be a useful adjunctive diagnostic tool to select optimal treatment regimens for OSA patients with varying degrees of severity.

Aged↗
PubMed1997

Holistic approach to analysis of medical data: vulvar cancer.

This paper continues the series of studies introducing holistic approach to analysis of clinical data. Namely, besides the information regarding his/her disease, each hospitalized cancer patient also provides the variety of data regarding his/her psychological, cultural, social, economical, genetic, constitutional and medical background. The aim of this study was to introduce a holistic approach to analysis of medical data, in this case clinical data regarding cancer of the vulva. Such approach requires the collection of data regarding different aspects of the cancer patients, and after the satisfactory sample size is obtained (which should be at least five times greater than the number of examined patient characteristics), the performance of factor analysis. In this study, the authors have processed the data regarding 25 characteristics of all 755 vulvar cancer patients treated between 1938 and 1990 at the Department for Gynecological Oncology of the University Hospital for Gynecology and Obstetrics, Zagreb, Croatia. In factor analysis, the principal components were rotated after the initial extraction (the authors recommended the use of oblimin rotation) in order to obtain better ground for interpretation of the obtained results. The next step in this approach was the stepwise exclusion of characteristics with smallest commonality according to Kaiser-Meyer-Olkin criteria, and retaining the characteristics and components with the most significant impact on the explained system variance. When the number of principal components and initial analyzed characteristics was reduced to 3-4 and 7-10, respectively, the ultimate interpretations and conclusions were made. This approach outlined some clusters of correlations between medical data which are difficult to identify using other statistical procedures, primarily the impacts of various socioeconomic and hereditary-constitutional variables on overall survival.

Adult↗
PubMed1997

Holistic approach to analysis of medical data: cancer of the corpus uteri.

Besides the information regarding his/her disease, each hospitalized cancer patient also provides the variety of data regarding his/her psychological, cultural, social, economical, genetic, constitutional and medical background. The aim of this study was to introduce a holistic approach to analysis of medical data, in this case clinical data regarding cancer of the corpus uteri. Such approach requires the collection of data regarding different aspects of the cancer patient, and after the satisfactory sample size is obtained (which should be at least five times greater than the number of examined patient characteristics), the performance of factor analysis. In this study, the authors have processed the data regarding 25 characteristics of 928 corpus uteri cancer patients treated between 1980 and 1990 at the Department for Gynecological Oncology of the University Hospital for Gynecology and Obstetrics, Zagreb, Croatia. In factor analysis, the principal components were rotated after the initial extraction (the authors recommended the use of oblimin rotation) in order to obtain better ground for interpretation of the obtained results. The next step in this approach was the stepwise exclusion of characteristics with smallest communalities according to Kaiser-Meyer-Olkin criteria, and retaining the characteristics and components with the most significant impact on the explained system variance. When the number of principal components and initial analyzed characteristics was reduced to 3-4 and 7-10, respectively, the ultimate interpretations and conclusions were made. This approach outlined some clusters of correlations between medical data which are difficult to identify using other statistical procedures, primarily the impacts of various socioeconomic and hereditary-constitutional variables on overall survival.

Factor Analysis, Statistical↗
PubMed2005

Symptom clusters as predictors of late response to antidepressant treatment.

OBJECTIVE: While there is some indication from studies in the acute phase of antidepressant treatment that there are differences in the timing of improvement in symptoms, relatively little work has explored the patterns of change for specific symptom clusters and the predictability of these changes to signal eventual response during the acute phase of treatment. This article investigates the use of clusters of symptoms on the 17-item Hamilton Rating Scale for Depression (HAM-D-17) to define the pattern of late response versus nonresponse to antidepressant medication. METHOD: Using principal component analysis, the HAM-D-17 was divided into 4 symptom clusters (mood, sleep/psychic anxiety, appetite, and somatic anxiety/weight). Data for 996 patients with major depressive disorder (DSM-III-R criteria), who participated in a 12-week acute phase study with nefazodone, were subjected to a post hoc analysis of changes in symptom cluster scores. Patients were divided into 3 groups: early responders (< 4 weeks), late responders (4-12 weeks), and nonresponders (> 12 weeks) as defined by < 50% reduction in HAM-D-17 scores from baseline. The late-responder and nonresponder groups were subjected to the principal component analysis. Data were collected from October 1992 to November 1994. RESULTS: There were significant differences in the pattern of symptom change on the mood cluster (weeks 3-4) (p < .0001), the sleep/psychic anxiety cluster (weeks 3-4) (p < .003), and the somatic anxiety/weight cluster (weeks 3-4) (p < .01) for the late responders compared to the nonresponders. Using change scores, a discriminant function analysis correctly assigned 127 of the 182 late responders and 85 of the 133 nonresponders, or 70% of the late responders and 64% of the nonresponders, to their final response groups. CONCLUSION: Monitoring changes in symptom clusters from the HAM-D-17 during this crucial early stage (first 4 weeks) can be used to distinguish late responders (after week 4) from nonresponders. Successful identification of nonresponders based on symptom cluster change in the first 4 weeks would facilitate a shortening of an ineffective treatment trial and allow for necessary changes in treatment strategy, helping physicians more closely follow treatment guidelines.

Adult↗
PubMed2005

Multivariate statistical methods for evaluating biodegradation of mineral oil.

Two methods were developed for evaluating natural attenuation and bioremediation of mineral oil after environmental spills and during in vitro experiments. Gas chromatography-mass spectrometry (GC-MS) in selected ion monitoring (SIM) mode was used to obtain compound-specific data. The chromatographic data were then preprocessed either by calculating the first derivative, retention time alignment and normalization or by peak identification, quantification and calculation of diagnostic ratios within homologue series of polycyclic aromatic compounds (PACs). Finally, principal component analysis (PCA) was applied to the preprocessed chromatograms or diagnostic ratios to study the fate of the oil. The methods were applied to data from an in vitro biodegradation experiment with a North Sea crude oil exposed to three mixtures of bacterial strains: R (alkane degraders and surfactant producers), U (PAC degraders) and M (mixture of R- and U-strains) over a 1-year-period with five sampling times. Assessment of variation in degradability within isomer groups of methylfluorenes (m/z 180), methylphenanthrenes (m/z 192) and methyldibenzothiophenes (m/z 198) was used to evaluate the effects of microbial degradation on the composition of the oil. The two evaluation methods gave comparable results. In the objective pattern matching approach, principal component 1 (PC1) described the general changes in the isomer abundances, whereas M samples were separated from U and R samples along PC2. Furthermore, in the diagnostic ratio approach, a third component (PC3) could be extracted; although minor, it separated R samples from U and M samples. These results demonstrated that the two methods were able to differentiate between the effects due to the different bacterial activities, and that bacterial strain mixtures affected the PAC isomer patterns in different ways in accordance with their different metabolic capabilities.

Bacteria↗
PubMed2005

Variability, repeatability and phenotypic relationships of several characteristics of production and semen quality in rabbit.

A total of 2140 ejaculates from 156 adult males pertaining to four groups of bucks were analysed and the following traits were recorded: pH, ejaculate volume (V), mass motility (Mm), individual motility (Mi), concentration (Cn), total number of spermatozoa per ejaculate (TSE), percentage of sperm viability (Vi), percentage of sperm with acrosome integrity (NAR), percentage of sperm normalcy (Nr), percentage of sperm morphological abnormalities of head (H), neck-midpiece (Nm) and tail (T) and presence of proximal and distal cytoplasmic droplet (Dp, Dd). Principal component (PC) analysis and phenotypic correlations were performed in order to examine the relationships between qualitative and quantitative traits of rabbit semen. The repeatability of the traits measured was also estimated. Phenotypic correlations between sperm traits were estimated as the residual correlation from an analysis of variance, including the effects of: genetic type of the male, order of the ejaculate, day of collection and the permanent non-additive random effect of the male to which the observation corresponds. The repeatability of these traits was analysed separately, in a set of univariate analyses, using VCE software. The previously defined mixed model was used for this analysis. The principal component analysis was performed using the Princomp procedure of the SAS v.8 package. The first four PC explained 62% of total variation: 23%, 18%, 12% and 8%, respectively. Percentage of sperm viability, NAR, Nr, T and Nm were the predominant variables in the first PC. Mass motility, Mi, pH, Cn and TSE were located in the second. Percentage of sperm with the presence of proximal and distal cytoplasmic droplet, NAR, Vi and Nr were the predominant traits in the third and V defined the fourth. Repeatability of semen quality traits was moderate for most of the traits. The highest values (about 0.45) corresponded to V, Cn, Nr and Dp and the lowest (about 0.10) to H and Nm. Repeatability of the first ejaculate was greater than that of the second for pH, Mm, Mi, H, Dp and Dd.

Acrosome↗
PubMed2005

A multivariate approach for processing magnetization effects in triggered event-related functional magnetic resonance imaging time series.

Triggered event-related functional magnetic resonance imaging requires sparse intervals of temporally resolved functional data acquisitions, whose initiation corresponds to the occurrence of an event, typically an epileptic spike in the electroencephalographic trace. However, conventional fMRI time series are greatly affected by non-steady-state magnetization effects, which obscure initial blood oxygen level-dependent (BOLD) signals. Here, conventional echo-planar imaging and a post-processing solution based on principal component analysis were employed to remove the dominant eigenimages of the time series, to filter out the global signal changes induced by magnetization decay and to recover BOLD signals starting with the first functional volume. This approach was compared with a physical solution using radiofrequency preparation, which nullifies magnetization effects. As an application of the method, the detectability of the initial transient BOLD response in the auditory cortex, which is elicited by the onset of acoustic scanner noise, was used to demonstrate that post-processing-based removal of magnetization effects allows to detect brain activity patterns identical with those obtained using the radiofrequency preparation. Using the auditory responses as an ideal experimental model of triggered brain activity, our results suggest that reducing the initial magnetization effects by removing a few principal components from fMRI data may be potentially useful in the analysis of triggered event-related echo-planar time series. The implications of this study are discussed with special caution to remaining technical limitations and the additional neurophysiological issues of the triggered acquisition.

Artifacts↗
PubMed2005

Molecular phenotyping of human endometrium distinguishes menstrual cycle phases and underlying biological processes in normo-ovulatory women.

Histological evaluation of endometrium has been the gold standard for clinical diagnosis and management of women with endometrial disorders. However, several recent studies have questioned the accuracy and utility of such evaluation, mainly because of significant intra- and interobserver variations in histological interpretation. To examine the possibility that biochemical or molecular signatures of endometrium may prove to be more useful, we have investigated whole-genome molecular phenotyping (54,600 genes and expressed sequence tags) of this tissue sampled across the cycle in 28 normo-ovulatory women, using high-density oligonucleotide microarrays. Unsupervised principal component analysis of all samples revealed that samples self-cluster into four groups consistent with histological phenotypes of proliferative (PE), early-secretory (ESE), mid-secretory (MSE), and late-secretory (LSE) endometrium. Independent hierarchical clustering analysis revealed equivalent results, with two major dendrogram branches corresponding to PE/ESE and MSE/LSE and sub-branching into the four respective phases with heterogeneity among samples within each sub-branch. K-means clustering of genes revealed four major patterns of gene expression (high in PE, high in ESE, high in MSE, and high in LSE), and gene ontology analysis of these clusters demonstrated cycle-phase-specific biological processes and molecular functions. Six samples with ambiguous histology were identically assignable to a cycle phase by both principal component analysis and hierarchical clustering. Additionally, pairwise comparisons of relative gene expression across the cycle revealed genes/families that clearly distinguish the transitions of PE-->ESE, ESE-->MSE, and MSE-->LSE, including receptomes and signaling pathways. Select genes were validated by quantitative RT-PCR. Overall, the results demonstrate that endometrial samples obtained by two different sampling techniques (biopsy and curetting hysterectomy specimens) from subjects who are as normal as possible in a human study and including those with unknown histology, can be classified by their molecular signatures and correspond to known phases of the menstrual cycle with identical results using two independent analytical methods. Also, the results enable global identification of biological processes and molecular mechanisms that occur dynamically in the endometrium in the changing steroid hormone milieu across the menstrual cycle in normo-ovulatory women. The results underscore the potential of gene expression profiling for developing molecular diagnostics of endometrial normalcy and abnormalities and identifying molecular targets for therapeutic purposes in endometrial disorders.

Adult↗
PubMed2004

Plasma and hypothalamic peptide-hormone levels regulating somatotroph function and energy balance in fed and fasted states: a comparative study in four strains of rats.

Both growth hormone (GH)/insulin growth factor (IGF)-1 axis and energy balance have been implicated in longevity independently. The aim of the present study was to characterize the effect of a 72-h fasting period at 3 months of age in four different rat strains: (i) Wistar and (ii) Fischer 344 rats, which develop obesity with age, and (iii) Brown Norway and (iv) Lou C rats, which do not. Wistar rats ate more, were significantly bigger, and presented with higher plasma leptin and lower ghrelin levels and hypothalamic growth hormone-releasing hormone (GHRH) content than rats from the three other strains. Plasma insulin and IGF-1 levels were lower in Brown Norway and Lou C rats, and somatostatin content was lower in Brown Norway rats only. Glycaemia was lower in Lou C rats that displayed a lower relative food intake compared to Fischer and Wistar rats. Brown Norway rats showed a greater caloric efficiency than the three other strains. Concerning major hypothalamic neuropeptides implicated in feeding, similar amounts were detected in the four strains for neuropeptide Y, agouti-related peptide, galanin, melanin-concentrating hormone, alpha-melanocortin-stimulating hormone (alpha-MSH) and corticotropin-releasing hormone. Orexin A appeared to be slightly elevated in Fischer rats and cocaine amphetamine-regulated transcript (CART)(55-102) diminished in Brown Norway. At the mRNA level, orexin A, GHSR1, alpha-MSH and CART expression were higher in Wistar and Lou C rats. Principal component analysis confirmed the presence of two main factors in the ad libitum rat population; the first being associated with growth-related parameters and the second being associated with food intake regulation. Hypothalamic GHRH and somatostatin content were positively correlated with feeding-related neuropeptides such as alpha-MSH for GHRH, and orexin A and CART for both peptides. Plasma ghrelin levels were negatively correlated with leptin and IGF-1 levels. Finally, a 72-h fasting period affected minimally body weight, plasma IGF-1 and leptin levels in Lou C rats compared to the three other strains, and plasma insulin levels were less affected in Brown Norway rats. In conclusion, Wistar shorter life span is consistent with its already fatter phenotype at 3 months of age. In terms of IGF-1, glycaemia and leptin responses to fasting, the Lou strain, which presents with a low food intake/body weight and caloric efficiency, is the least affected. The link between food intake regulation, GH axis and ageing is further demonstrated by principal component analysis, where GHRH and somatostatin were found to be strongly associated with energy homeostasis parameters.

Aging↗
PubMed2005

Patterns and localization of gene expression during intramembranous bone regeneration in the rat femoral marrow ablation model.

Tissue formation and repair are dependent upon cascades of biological events, but the signals involved and the possible gene coexpression patterns during intramembranous bone repair are only poorly understood. We sought to place this mode of regeneration in context by profiling quantitative gene expression for a panel of 39 genes between days 1 and 14 following rat femoral marrow ablation. In situ hybridization was employed to localize a subset of genes. Additionally, principal components analysis was conducted to identify underlying factors suggestive of coexpression patterns. During inflammation (days 1-5), several genes, including cyclooxygenase-1 and -2, showed downregulation. Other proinflammatory cytokines, tumor necrosis factor-alpha and interleukin-1beta, exhibited increasing levels around day 5. During repair (days 3-10), growth factors, receptors, and inhibitor genes for transforming growth factor- beta; basic fibroblast growth factor; bone morphogenetic proteins 2, 4, and 7; vascular endothelial growth factor; and insulin-like growth factor-I were upregulated. In addition, the gene for core binding factor-alpha1 and markers of osteoblast function such as alkaline phosphatase, collagen type I, osteonectin, osteopontin, and osteocalcin had peak expression at day 5 or 7. The remodeling phase (days 10-14) was characterized by peaks for cytokines associated with osteoclastic activity including receptor activator of nuclear factor-kappaB, receptor activator of nuclear factor-kappaB ligand (RANKL), cathepsin K, tumor necrosis factor-alpha, interleukin-6, and cyclooxygenase-2. In situ hybridization showed that the most common sites of increased signal were within osteoblastic cells on trabecular and endosteal surfaces. Principal components analysis identified eight underlying factors that together explained over 80% of the variance in the data.

Animals↗
PubMed2025

A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.

BACKGROUND: DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of training epigenetic predictors on principal components. METHODOLOGY/FINDINGS: We developed a pipeline to simultaneously train three epigenetic predictors; a traditional CpG Clock, a PCA Clock, and a SuperLearner PCA Clock (SL PCA). We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. We used correlation coefficients and median absolute error to assess fit between predicted and observed measures, as well as agreement between duplicates. The SL PCA clocks improved fit with observed phenotypes relative to the PCA clocks or CpG clocks across several datasets. We found evidence for higher agreement between duplicate samples run on alternate DNAm arrays when using SL PCA clocks relative to traditional methods. Analyses examining associations between relevant exposures and epigenetic age acceleration (EAA) produced more precise effect estimates when using predictions derived from SL PCA clocks. CONCLUSIONS: We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.

DNA Methylation↗
PubMed2001

Investigations into biochemical changes due to diurnal variation and estrus cycle in female rats using high-resolution (1)H NMR spectroscopy of urine and pattern recognition.

Metabonomic methods utilizing (1)H NMR spectroscopy and pattern recognition analysis (NMR-PR) have been applied to investigate biochemical variation in a control population of female rats over time in relation to diurnal and estrus cycle fluctuations. Urine samples were collected twice daily (6 AM-6 PM and 6 PM-6 AM) from female rats (n = 10) for a period of 10 days. (1)H NMR spectroscopic analysis and PR were performed on each sample. Subtle differences in the endogenous metabolite excretion profiles of urine samples at the various stages of the estrus cycle were observed. The main inherent metabolic clustering in the principal components analysis (PCA) maps was related to interrat variation and was observed in the first two principal components (PCs), accounting for 66% of the variance in these data. Separation of urinary data according to time of sampling (day and night) was achieved in the lower PCs. Some of the differences in the urinary profiles of day and night samples causing this separation were attributed to the increase in metabolic activity of the rat during the night. Individual rat data were also mapped as a function of time, using PCA, to produce a metabolic trajectory, which in a number of cases facilitated separation of one or more stages of the estrus cycle. Several of the fluctuations observed between urine samples collected during the different stages of the estrus cycle may be related to hormone levels. Although variation in metabolite profiles relating to both diurnal and hormonal variation could be detected these perturbations were minor compared with the effects observed due to interrat variation. This is the first time that a hormonal cycle has been described for individuals based on NMR spectroscopic and multivariate analysis of metabolic data and shows the value of metabonomic methods in the investigation of physiological variation and rhythms.

Animals↗
PubMed1993

Pyrazine CH- and NH-acids. Antithrombotic activity and chromatographic behaviour.

1. A series of newly synthesized pyrazine CH- and NH-acids was subjected to analytical and pharmacological studies. 2. The compounds were chromatographed in HPLC systems employing three reversed-phase columns and methanol-buffer solvents of various composition at acidic, neutral and alkaline pH. 3. Chemometrical analysis by the principal component method allowed for ordering of the compounds on a plane determined by the first two principal component axes. 4. Pharmacological tests were done for representatives of the series of compounds. 5. An in vivo antithrombotic assay on mice proved diversified bioactivity within the group of agents. 6. Attempts were undertaken to relate chromatographic behaviour to antithrombotic activity. 7. Based on the results obtained, an approach was proposed to reduce the number of pharmacological tests in selecting the most promising agents.

Adenosine Diphosphate↗
PubMed2006

Morphometric changes in goat sperm heads induced by cryopreservation.

Two experiments were designed to evaluate the effect of cryopreservation on morphometric characteristics of the goat sperm head. To address this question, we evaluated the size of the sperm head in fresh control cells, post-cooling cells after equilibration with the glycerol preservation solution, and post-thawing cells. Assessment was by automated morphometric sperm head analysis (ASMA) using phase-contrast microscopy without staining. In the first experiment, ASMA was performed on heterospermic pooled samples (fresh, post-cooling after equilibration with the glycerol preservation solution and post-thawing): length, width, area and perimeter were measured. In the second experiment, sperm viability was assessed by Hoechst staining and head morphometry was carried out as before, simultaneously during the cryopreservation process, and the head size was identified for both live and dead spermatozoa. The data were analysed by principal component analysis (PCA). The purpose of PCA is to derive a small number of linear combinations (principal components) from a set of variables (length, width, area and perimeter), that retain as much of the information in the original variables as possible. The main findings that have emerged from this study are that (i) a simple procedure has been developed for measuring spermatozoa heads without staining, which minimises the possibility that sperm head dimensions were influenced by procedural artefacts; (ii) the dimensions of goat sperm heads after cryopreservation in skimmed milk-glucose medium were smaller than in fresh sperm, but this was due to the equilibration phase with the cryoprotectant and not to the cryopreservation process itself; and (iii) dead spermatozoa showed smaller heads than live sperm, consequent upon the loss of membrane function. No differences were observed between post-cooling cells after equilibration with the glycerol preservation solution and post-thawing spermatozoa and only minor osmotic differences between them and fresh sperm were observed.

Animals↗
PubMed2005

Structure and dynamics of an RNA tetraloop: a joint molecular dynamics and NMR study.

Molecular dynamics simulations of the RNA tetraloop 5'-CGCUUUUGCG-3' with high melting temperature and significant conformational heterogeneity in explicit water solvent are presented and compared to NMR studies. The NMR data allow for a detailed test of the theoretical model, including the quality of the force field and the conformational sampling. Due to the conformational heterogeneity of the tetraloop, high temperature (350 K) and locally enhanced sampling simulations need to be invoked. The Amber98 force field leads to a good overall agreement with experimental data. Based on NMR data and a principal component analysis of the 350 K trajectory, the dynamic structure of the tetraloop is revealed. The principal component free energy surface exhibits four minima, which correspond to well-defined conformational structures that differ mainly by their base stacking in the loop region. No correlation between the motion of the sugar rings and the stacking dynamics of the loop bases is found.

Nuclear Magnetic Resonance, Biomolecular↗