Time course of meiotic spindle development in MII oocytes

Zygote ◽  
2010 ◽  
Vol 19 (1) ◽  
pp. 55-62 ◽  
Author(s):  
Suha Kilani ◽  
Simon Cooke ◽  
Michael Chapman
Keyword(s):  
Time Course ◽  
Polarized Light ◽  
Time Dependent ◽  
Meiotic Spindle ◽  
Optimal Time ◽  
Stimulation Protocol ◽  
Time Intervals ◽  
Spindle Development ◽  
Microscopy Images ◽  
Over Time

SummaryThe aim of this study was to examine changes in meiotic spindle morphology over time to potentially optimize timing for ICSI. Using polarized light microscopy, images of MII oocytes were captured after retrieval of oocytes in stimulated cycles at six time intervals in culture: 36–36.5 h, 36.5–37.0 h, 38–38.5 h, 39–39.5 h, 40–40.5 h and 40.5–41 h post hCG. Captured images were analysed for spindle presence and their retardance. Results showed that spindles were detected in 58% (45/78) of oocytes at 36–36.5 h. This percentage rose to a peak (96% vs. 58%, p < 0.001) at 39–39.5 h and stabilized between 39–40.5 h post trigger then significantly declined at 40.5–41 h post hCG (96% vs. 77%, p < 0.001). Average spindle retardance increased from 36–36.5 h (1.8 ± 0.7 nm) until it peaked at 39–40.5 h (3.8 ± 0.8 nm, p < 0.0001) and then declined significantly after 40.5–41 h (3.2 ± 0.9 nm, p = 0.0001). These results show that the meiotic spindle appearance is time dependent with the majority of oocytes having detectable spindles and highest retardance between 39–40.5 h post hCG under currently used stimulation protocol after which they start to disaggregate. 39–40.5 h post hCG may be the optimal time for ICSI.

Evaluating the Effect of Incidents on Freeway Facilities and Updating the Incident Capacity Adjustments for HCM

2020 ◽  
pp. 036119812094953
Author(s):  
Jeremy Addison ◽  
Seyedbehzad Aghdashi ◽  
Nagui M. Rouphail
Keyword(s):  
Calibration Method ◽  
Time Dependent ◽  
Optimal Time ◽  
Incident Management ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Management Actions ◽  
Look Up Table ◽  
Adjustment Factors ◽  
Over Time

This paper investigates the effect of incidents on freeway segment capacity. Currently, the Highway Capacity Manual (HCM) provides a look-up table linking the remaining segment capacity fraction during an incident to the total and closed number of lanes on the segment. In reality, segment capacity during an incident will tend to vary over time, with the most severe effects felt early on before any type of response is initiated, with congestion progressively improving as the appropriate incident management actions are implemented. By applying a genetic algorithm calibration method on each incident day and calibrating the incident capacity adjustment factors (CAFs), optimal time-dependent CAFs were derived that best represented the effect of incidents on the freeway segment capacity. By analyzing the optimal CAFs, the strongest relationship was revealed to be between the optimal time-dependent CAF and the temporal progression of the incident. A regression model was developed to represent this behavior. This was formulated in a manner that can directly adjust the current HCM’s fixed CAF values (for a specific lane closure configuration) for modeling incidents both in single day, seed file application, or for an entire year reliability analysis. A portion of WB I-540 in Raleigh, NC was selected as the study area in which the proposed method was tested. Between January 2014 and December 2018, the team identified 22 isolated incidents (away from the recurring congestion period) that closed one or two lanes of traffic, creating a distinct congestion pattern.

scholarly journals Detection of Acetaminophen and Its Glucuronide in Fingerprint by SALDI Mass Spectrometry Using Zeolite and Study of Time-Dependent Changes in Detected Ion Amount

Analytica ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 66-75
Author(s):  
Toshiki Horikoshi ◽  
Chihiro Kitaoka ◽  
Yosuke Fujii ◽  
Takashi Asano ◽  
Jiawei Xu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Glucuronic Acid ◽  
Laser Desorption ◽  
The Body ◽  
Time Dependent ◽  
Laser Desorption Ionization ◽  
Fingerprint Analysis ◽  
Desorption Ionization ◽  
Acid Conjugate ◽  
Over Time

The ingredients of an antipyretic (acetaminophen, AAP) and their metabolites excreted into fingerprint were detected by surface-assisted laser desorption ionization (SALDI) mass spectrometry using zeolite. In the fingerprint taken 4 h after AAP ingestion, not only AAP but also the glucuronic acid conjugate of AAP (GAAP), caffeine (Caf), ethenzamide (Eth), salicylamide (Sala; a metabolite of Eth), and urea were detected. Fingerprints were collected over time to determine how the amounts of AAP and its metabolite changed with time, and the time dependence of the peak intensities of protonated AAP and GAAP was measured. It was found that the increase of [GAAP+H]+ peak started later than that of [AAP+H]+ peak, reflecting the metabolism of AAP. Both AAP and GAAP reached maximum concentrations approximately 3 h after ingestion, and were excreted from the body with a half-life of approximately 3.3 h. In addition, fingerprint preservation was confirmed by optical microscopy, and fingerprint shape was retained even after laser irradiation of the fingerprint. Our method may be used in fingerprint analysis.

scholarly journals Risk Factors for Prostate Cancer Detection After a Negative Biopsy: A Novel Multivariable Longitudinal Approach

2010 ◽  
Vol 28 (10) ◽  
pp. 1714-1720 ◽  
Author(s):  
Peter H. Gann ◽  
Angela Fought ◽  
Ryan Deaton ◽  
William J. Catalona ◽  
Edward Vonesh
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Specific Antigen ◽  
Time Dependent ◽  
Negative Biopsy ◽  
Gland Volume ◽  
Piecewise Exponential ◽  
Over Time ◽  
Negative Biopsies

Purpose To introduce a novel approach for the time-dependent quantification of risk factors for prostate cancer (PCa) detection after an initial negative biopsy. Patients and Methods Data for 1,871 men with initial negative biopsies and at least one follow-up biopsy were available. Piecewise exponential regression models were developed to quantify hazard ratios (HRs) and define cumulative incidence curves for PCa detection for subgroups with specific patterns of risk factors over time. Factors evaluated included age, race, serum prostate-specific antigen (PSA) concentration, PSA slope, digital rectal examination, dysplastic glands or prostatitis on biopsy, ultrasound gland volume, urinary symptoms, and number of negative biopsies. Results Four hundred sixty-five men had PCa detected, after a mean follow-up time of 2.8 years. All of the factors were independent predictors of PCa detection except for PSA slope, as a result of its correlation with time-dependent PSA level, and race. PSA (HR = 3.90 for > 10 v 2.5 to 3.9 ng/mL), high-grade prostatic intraepithelial neoplasia/atypical glands (HR = 2.97), gland volume (HR = 0.39 for > 50 v < 25 mL), and number of repeat biopsies (HR = 0.36 for two v zero repeat biopsies) were the strongest predictors. Men with high-risk versus low-risk event histories had a 20-fold difference in PCa detection over 5 years. Conclusion Piecewise exponential models provide an approach to longitudinal analysis of PCa risk that allows clinicians to see the interplay of risk factors as they unfold over time for individual patients. With these models, it is possible to identify distinct subpopulations with dramatically different needs for monitoring and repeat biopsy.

Pulsatile Pressure and Flow in the Skeletal Muscle Microcirculation

1990 ◽  
Vol 112 (4) ◽  
pp. 437-443 ◽  
Author(s):  
Shou-Yan Lee ◽  
G. W. Schmid-Scho¨nbein
Keyword(s):  
Skeletal Muscle ◽  
Arterial Pressure ◽  
Time Course ◽  
Venous Pressure ◽  
Time Dependent ◽  
Physiological Importance ◽  
Pulsatile Pressure ◽  
Theoretical Predictions ◽  
Skeletal Muscle Microcirculation

Although blood flow in the microcirculation of the rat skeletal muscle has negligible inertia forces with very low Reynolds number and Womersley parameter, time-dependent pressure and flow variations can be observed. Such phenomena include, for example, arterial flow overshoot following a step arterial pressure, a gradual arterial pressure reduction for a step flow, or hysteresis between pressure and flow when a pulsatile pressure is applied. Arterial and venous flows do not follow the same time course during such transients. A theoretical analysis is presented for these phenomena using a microvessel with distensible viscoelastic walls and purely viscous flow subject to time variant arterial pressures. The results indicate that the vessel distensibility plays an important role in such time-dependent microvascular flow and the effects are of central physiological importance during normal muscle perfusion. In-vivo whole organ pressure-flow data in the dilated rat gracilis muscle agree in the time course with the theoretical predictions. Hemodynamic impedances of the skeletal muscle microcirculation are investigated for small arterial and venous pressure amplitudes superimposed on an initial steady flow and pressure drop along the vessel.

scholarly journals Jonckheere–Terpstra–Kendall-based non-parametric analysis of temporal differential gene expression

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Hitoshi Iuchi ◽  
Michiaki Hamada
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Time Course ◽  
Time Series Data ◽  
Expression Patterns ◽  
Detection Methods ◽  
Series Data ◽  
Expression Levels ◽  
Over Time ◽  
Non Parametric

Abstract Time-course experiments using parallel sequencers have the potential to uncover gradual changes in cells over time that cannot be observed in a two-point comparison. An essential step in time-series data analysis is the identification of temporal differentially expressed genes (TEGs) under two conditions (e.g. control versus case). Model-based approaches, which are typical TEG detection methods, often set one parameter (e.g. degree or degree of freedom) for one dataset. This approach risks modeling of linearly increasing genes with higher-order functions, or fitting of cyclic gene expression with linear functions, thereby leading to false positives/negatives. Here, we present a Jonckheere–Terpstra–Kendall (JTK)-based non-parametric algorithm for TEG detection. Benchmarks, using simulation data, show that the JTK-based approach outperforms existing methods, especially in long time-series experiments. Additionally, application of JTK in the analysis of time-series RNA-seq data from seven tissue types, across developmental stages in mouse and rat, suggested that the wave pattern contributes to the TEG identification of JTK, not the difference in expression levels. This result suggests that JTK is a suitable algorithm when focusing on expression patterns over time rather than expression levels, such as comparisons between different species. These results show that JTK is an excellent candidate for TEG detection.

Decomposition of Growth Curves into Growth Rate and Acceleration: a Novel Procedure to Monitor Bacterial Growth and the Time-Dependent Effect of Antimicrobials

2021 ◽  
Author(s):  
M. Luisa Navarro-Pérez ◽  
M. Coronada Fernández-Calderón ◽  
Virginia Vadillo-Rodríguez
Keyword(s):  
Growth Rate ◽  
Mathematical Models ◽  
Bacterial Growth ◽  
Time Course ◽  
Antimicrobial Agents ◽  
Numerical Procedure ◽  
Growth Curves ◽  
Predictive Microbiology ◽  
Insight Into ◽  
Over Time

In this paper, a simple numerical procedure is presented to monitor the growth of Streptococcus sanguinis over time in the absence and presence of propolis, a natural antimicrobial. In particular, it is shown that the real-time decomposition of growth curves obtained through optical density measurements into growth rate and acceleration can be a powerful tool to precisely assess a large range of key parameters [ i.e. lag time ( t 0 ), starting growth rate ( γ 0 ), initial acceleration of the growth ( a 0 ), maximum growth rate ( γ max ), maximum acceleration ( a max ) and deceleration ( a min ) of the growth and the total number of cells at the beginning of the saturation phase ( N s )] that can be readily used to fully describe growth over time. Consequently, the procedure presented provides precise data of the time course of the different growth phases and features, which is expected to be relevant, for instance, to thoroughly evaluate the effect of new antimicrobial agents. It further provides insight into predictive microbiology, likely having important implications to assumptions adopted in mathematical models to predict the progress of bacterial growth. Importance: The new and simple numerical procedure presented in this paper to analyze bacterial growth will possibly allow identifying true differences in efficacy among antimicrobial drugs for their applications in human health, food security, and environment, among others. It further provides insight into predictive microbiology, likely helping in the development of proper mathematical models to predict the course of bacterial growth under diverse circumstances.

Time-dependent progression of neurogenic lower urinary tract dysfunction after spinal cord injury in the mouse model

2021 ◽  
Author(s):  
Tetsuichi Saito ◽  
Daisuke Gotoh ◽  
Naoki Wada ◽  
Pradeep Tyagi ◽  
Tomonori Minagawa ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Time Course ◽  
Time Dependent ◽  
Lower Urinary Tract Dysfunction ◽  
Emg Activity ◽  
Mrna Levels ◽  
Mechanosensitive Channels ◽  
Reduction Time ◽  
Cord Injury

This study evaluated the time-course changes in bladder and external urinary sphincter (EUS) activity as well as the expression of mechanosensitive channels in lumbosacral dorsal root ganglia (DRG) after spinal cord injury (SCI). Female C57BL/6N mice in the SCI group underwent transection of the Th8/9 spinal cord. Spinal intact mice and SCI mice at 2, 4 and 6 weeks post SCI were evaluated by single-filling cystometry and EUS-electromyography (EMG). In another set of mice, the bladder and L6-S1 DRG were harvested for protein and mRNA analyses. In SCI mice, non-voiding contractions was confirmed at 2 weeks post-SCI, and did not increase over time to 6 weeks. In 2-weeks SCI mice, EUS-EMG measurements revealed detrusor-sphincter dyssynergia (DSD), but periodic EMG reductions during bladder contraction were hardly observed. At 4 weeks, SCI mice showed increases of EMG activity reduction time with increased voiding efficiency (VE). At 6 weeks, SCI mice exhibited a further increase in EMG reduction time. RT-PCR of L6-S1 DRG showed increased mRNA levels of TRPV1 and ASIC1-3 in SCI mice with a decrease of ASIC2-3 at 6 weeks compared to 4 weeks whereas Piezo2 showed a slow increase at 6 weeks. Protein assay showed the SCI-induced overexpression of bladder BDNF with a time-dependent decrease post SCI. These results indicate that detrusor overactivity is established in the early phase whereas DSD is completed later at 4 weeks with an improvement at 6 weeks post SCI, and that mechanosensitive channels may be involved in the time-dependent changes.

scholarly journals A Tutorial on Evaluating the Time-Varying Discrimination Accuracy of Survival Models Used in Dynamic Decision Making

2018 ◽  
Vol 38 (8) ◽  
pp. 904-916 ◽  
Author(s):  
Aasthaa Bansal ◽  
Patrick J. Heagerty
Keyword(s):  
Decision Making ◽  
Statistical Methods ◽  
Sensitivity And Specificity ◽  
Prognostic Model ◽  
Dynamic Decision Making ◽  
Time Dependent ◽  
Survival Models ◽  
Biliary Cirrhosis ◽  
Time Varying ◽  
Over Time

Many medical decisions involve the use of dynamic information collected on individual patients toward predicting likely transitions in their future health status. If accurate predictions are developed, then a prognostic model can identify patients at greatest risk for future adverse events and may be used clinically to define populations appropriate for targeted intervention. In practice, a prognostic model is often used to guide decisions at multiple time points over the course of disease, and classification performance (i.e., sensitivity and specificity) for distinguishing high-risk v. low-risk individuals may vary over time as an individual’s disease status and prognostic information change. In this tutorial, we detail contemporary statistical methods that can characterize the time-varying accuracy of prognostic survival models when used for dynamic decision making. Although statistical methods for evaluating prognostic models with simple binary outcomes are well established, methods appropriate for survival outcomes are less well known and require time-dependent extensions of sensitivity and specificity to fully characterize longitudinal biomarkers or models. The methods we review are particularly important in that they allow for appropriate handling of censored outcomes commonly encountered with event time data. We highlight the importance of determining whether clinical interest is in predicting cumulative (or prevalent) cases over a fixed future time interval v. predicting incident cases over a range of follow-up times and whether patient information is static or updated over time. We discuss implementation of time-dependent receiver operating characteristic approaches using relevant R statistical software packages. The statistical summaries are illustrated using a liver prognostic model to guide transplantation in primary biliary cirrhosis.

Sleep Disorder Over Time: Psychiatric Correlates Among Males

1980 ◽  
Vol 136 (5) ◽  
pp. 456-462 ◽  
Author(s):  
Hervey Sweetwood ◽  
Igor Grant ◽  
Daniel F. Kripke ◽  
Marvin S. Gerst ◽  
Joel Yager
Keyword(s):  
Prospective Study ◽  
Sleep Disorder ◽  
Sleep Disturbances ◽  
Time Course ◽  
Psychiatric Symptomatology ◽  
Over Time

SummaryThis 18 month prospective study assessed the time course of sleep disturbances in 85 male psychiatric out-patients and 103 male non-patients. Over one-third of the patients and 5 per cent of the non-patients reported frequent symptoms of insomnia during at least 14 of the 18 months. Frequency and chronicity of insomnia were strongly associated with intensity of psychiatric symptomatology, but not with diagnosis. Minor tranquillizers and hypnotics were used frequently by patients and occasionally by non-patients, but there was little indication that they altered the course of insomnia.

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