scholarly journals Use of computer-assisted sperm motility assessment and multivariate pattern analysis to characterize ejaculate quality in Mohor gazelles (Gazella dama mhorr): effects of body weight, electroejaculation technique and short-term semen storage

Reproduction ◽  
2001 ◽  
Vol 122 (2) ◽  
pp. 265-273
Author(s):  
T Abaigar
Keyword(s):  
Body Weight ◽  
Sperm Motility ◽  
Pattern Analysis ◽  
Computer Assisted ◽  
Multivariate Pattern Analysis ◽  
Short Term ◽  
Semen Storage ◽  
Multivariate Pattern

scholarly journals Use of computer-assisted sperm motility assessment and multivariate pattern analysis to characterize ejaculate quality in Mohor gazelles (Gazella dama mhorr): effects of body weight, electroejaculation technique and short-term semen storage

Reproduction ◽  
2001 ◽  
pp. 265-273 ◽  
Author(s):  
T Abaigar ◽  
M Cano ◽  
AR Pickard ◽  
WV Holt
Keyword(s):  
Body Weight ◽  
Plasma Membrane ◽  
Sperm Motility ◽  
Pattern Analysis ◽  
Semen Quality ◽  
Computer Assisted ◽  
Short Term ◽  
Non Linear ◽  
Maximum Voltage ◽  
Acrosomal Integrity

Subjective and objective semen assessments were performed on 18 male Mohor gazelles (Gazella dama mhorr). Sperm motility assessments combined with sperm plasma membrane and acrosomal integrity evaluations were undertaken as part of a captive breeding programme. The primary objective was to test methodology for short-term preservation of gazelle semen for artificial insemination (storage in N-[Tris(hydroxymethyl)methyl]-2-aminoethanesulphonic acid-Tris diluent (TEST) for up to 96 h at 17 degrees C). However, the secondary objective was to investigate phenotypic and genotypic influences on semen quality within this small population, which was established in 1971 with only 12 genetic founders. Sperm motility was measured by computer-assisted semen assessment and the data were analysed using a pattern analysis technique to detect and quantify naturally occurring sperm subpopulations within the semen samples. Four sperm subpopulations distinguishable by their motion characteristics were detected. The relative frequencies of two subpopulations (population 2: highly motile, non-linear; and population 4: poorly motile, non-linear) in fresh semen were correlated with the maximum voltage used during electroejaculation. The frequency of subpopulation 2 was negatively correlated with maximum voltage (r = -0.875, P < 0.0001) and the frequency of subpopulation 4 was positively correlated (r = 0.727, P < 0.005). The frequencies of all subpopulations varied significantly among the animals sampled (chi-squared = 2577.6, degrees of freedom = 54, P < 0.0001) and subpopulation 4 was also correlated with body weight (r = -0.59, P < 0.005). Semen stored at 17 degrees C retained motility, plasma membrane and acrosomal integrity for 48 h, but these measures decreased thereafter. The frequency of a sperm subpopulation showing uncoordinated but active motility increased significantly over the first 48 h and then decreased.

231 SPERM SUBPOPULATIONS IN THE KOALA (PHASCOLARCTOS CINEREUS) EJACULATE

2009 ◽  
Vol 21 (1) ◽  
pp. 213
Author(s):  
N. Satake ◽  
S. D. Johnston ◽  
W. V. Holt
Keyword(s):  
Sperm Motility ◽  
Sperm Head ◽  
Computer Assisted ◽  
Multivariate Pattern Analysis ◽  
Phascolarctos Cinereus ◽  
Non Linear ◽  
Group 3 ◽  
Group 2 ◽  
Head Morphology ◽  
Multivariate Pattern

Koala semen contains a heterogeneous mixture of sperm morphotypes, mainly attributable to extreme degree of shape variability displayed by the hooked sperm head. By analogy with other species, we anticipate that the morphotypes may exhibit correspondingly different sperm-motility behaviors, largely caused by the differences in hydrodynamic interactions with the suspending media. This trend has been shown in human spermatozoa where motility behavior was demonstrably correlated with the sperm head morphology (Overstreet et al. 1981). In this study, we have investigated the heterogeneity of koala sperm motility profiles in semen in an effort to determine whether distinct sperm subpopulations within ejaculates are recognizable by the use of computer-assisted sperm motility analysis. Ejaculates from 5 males were collected by electroejaculation, then diluted and transported in Tris-citrate-glucose (TCG) diluent. Spermatozoa were washed through a 35–60% Percoll gradient to separate seminal plasma and the majority of the prostatic bodies from spermatozoa. Spermatozoa from the washed pellet were then diluted in TCG at 35°C, incubated for 10 min, and video recorded using a negative phase ×10 objective. Sperm motion parameters were then analyzed using the Hobson sperm tracker (Hobson Vision Systems, UK: Holt et al. 1996 J. Androl. 17, 587–596). Multivariate pattern analysis (PATN; CSIRO Australia; Abaigar 1999 Biol. Reprod. 60, 32–41) was used to distinguish 3 sperm subgroups, consistently shown in each ejaculate, within the data (1936 tracks × 6 kinetic parameters; VCL, VAP, MAD, BCF, ALH, LIN). After group allocation by PATN, all parameters showed significant differences between each of the groups (P < 0.0001). Group 1, approximately 25% of the sperm tracks, showed profiles of spermatozoa with fast, non-linear motility (VCL 106.88 ± 28.15; BCF 3.23 ± 3.81; LIN 14.08 ± 10.20). Group 2, approximately 27% of sperm tracks, showed profiles of fast, linear motility (VCL 63.92 ± 13.50; BCF 7.90 ± 3.42; LIN 28.10 ± 12.15). Group 3, 48% of sperm tracks, showed profiles of slow, non-linear or circular patterns of motility (VCL 39.05 ± 11.92; BCF 0.02 ± 0.35; LIN 5.15 ± 4.88). The recognition of 3 clearly identifiable subgroups supports our hypothesis that heterogeneity of sperm motility patterns exists within koala ejaculates. These may be a reflection of the heterogeneity in sperm-head morphotypes in koala semen, but that remains to be investigated in more detail. The clear distinctions between these groups, and the observation that all 3 subpopulations exist in each of the ejaculates, also suggest that the spermatozoa exhibit functional differences, possibly related to biochemical or maturational status. Many thanks to Dr. Michael Pyne and Dr. Vere Nicholson and their teams and animals at Currumbin Wildlife Sanctutary and Dreamwolrd QLD for all their help and support for the collection of samples.

scholarly journals Decoding Attended Information in Short-term Memory: An EEG Study

2013 ◽  
Vol 25 (1) ◽  
pp. 127-142 ◽  
Author(s):  
Joshua J. LaRocque ◽  
Jarrod A. Lewis-Peacock ◽  
Andrew T. Drysdale ◽  
Klaus Oberauer ◽  
Bradley R. Postle
Keyword(s):  
Neural Activity ◽  
Memory Trace ◽  
Pattern Analysis ◽  
Short Term Memory ◽  
Focus Of Attention ◽  
Multivariate Pattern Analysis ◽  
Short Term ◽  
Term Retention ◽  
Fmri Study ◽  
Multivariate Pattern

For decades it has been assumed that sustained, elevated neural activity—the so-called active trace—is the neural correlate of the short-term retention of information. However, a recent fMRI study has suggested that this activity may be more related to attention than to retention. Specifically, a multivariate pattern analysis failed to find evidence that information that was outside the focus of attention, but nonetheless in STM, was retained in an active state. Here, we replicate and extend this finding by querying the neural signatures of attended versus unattended information within STM with electroencephalograpy (EEG), a method sensitive to oscillatory neural activity to which the previous fMRI study was insensitive. We demonstrate that in the delay-period EEG activity, there is information only about memory items that are also in the focus of attention. Information about items outside the focus of attention is not detectable. This result converges with the fMRI findings to suggest that, contrary to conventional wisdom, an active memory trace may be unnecessary for the short-term retention of information.

scholarly journals A Multivariate Pattern Analysis of Metabolic Profile in Neurologically Impaired Children and Adolescents

Children ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 186
Author(s):  
Valeria Calcaterra ◽  
Giacomo Biganzoli ◽  
Gloria Pelizzo ◽  
Hellas Cena ◽  
Alessandra Rizzuto ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Glucose Metabolism ◽  
Children And Adolescents ◽  
Metabolic Profile ◽  
Children With Disabilities ◽  
Pattern Analysis ◽  
Multivariate Pattern Analysis ◽  
Neurologically Impaired ◽  
Multivariate Pattern ◽  
Impaired Children

Background: The prevalence of pediatric metabolic syndrome is usually closely linked to overweight and obesity; however, this condition has also been described in children with disabilities. We performed a multivariate pattern analysis of metabolic profiles in neurologically impaired children and adolescents in order to reveal patterns and crucial biomarkers among highly interrelated variables. Patients and methods: We retrospectively reviewed 44 cases of patients (25M/19F, mean age 12.9 ± 8.0) with severe disabilities. Clinical and anthropometric parameters, body composition, blood pressure, and metabolic and endocrinological assessment (fasting blood glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, triglycerides, glutamic oxaloacetic transaminase, glutamate pyruvate transaminase, gamma-glutamyl transpeptidase) were recorded in all patients. As a control group, we evaluated 120 healthy children and adolescents (61M/59F, mean age 12.9 ± 2.7). Results: In the univariate analysis, the children-with-disabilities group showed a more dispersed distribution, thus with higher variability of the features related to glucose metabolism and insulin resistance (IR) compared to the healthy controls. The principal component (PC1), which emerged from the PC analysis conducted on the merged dataset and characterized by these variables, was crucial in describing the differences between the children-with-disabilities group and controls. Conclusion: Children and adolescents with disabilities displayed a different metabolic profile compared to controls. Metabolic syndrome (MetS), particularly glucose metabolism and IR, is a crucial point to consider in the treatment and care of this fragile pediatric population. Early detection of the interrelated variables and intervention on these modifiable risk factors for metabolic disturbances play a central role in pediatric health and life expectancy in patients with a severe disability.

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