اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدImaging the Developing Heart: Synchronized Timelapse Microscopy During Developmental Changes
84
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
How do you use imaging to analyse the development of the heart, which not only changes shape but also undergoes constant, high-speed, quasi-periodic changes? We have integrated ideas from prospective and retrospective optical gating to capture long-term, phase-locked developmental time-lapse videos. In this paper we demonstrate the success of this approach over a key developmental time period: heart looping, where large changes in heart shape prevent previous prospective gating approaches from capturing phase-locked videos. We use the comparison with other approaches to in vivo heart imaging to highlight the importance of collecting the most appropriate data for the biological question.
قيم البحث
اقرأ أيضاً
The CVS is composed of numerous interacting and dynamically regulated physiological subsystems which each generate measurable periodic components such that the CVS can itself be presented as a system of weakly coupled oscillators. The interactions be
tween these oscillators generate a chaotic blood pressure waveform signal, where periods of apparent rhythmicity are punctuated by asynchronous behaviour. It is this variability which seems to characterise the normal state. We used a standard experimental data set for the purposes of analysis and modelling. Arterial blood pressure waveform data was collected from conscious mice instrumented with radiotelemetry devices over $24$ hours, at a $100$ Hz and $1$ kHz time base. During a $24$ hour period, these mice display diurnal variation leading to changes in the cardiovascular waveform. We undertook preliminary analysis of our data using Fourier transforms and subsequently applied a series of both linear and nonlinear mathematical approaches in parallel. We provide a minimalistic linear and nonlinear coupled oscillator model and employed spectral and Hilbert analysis as well as a phase plane analysis. This provides a route to a three way synergistic investigation of the original blood pressure data by a combination of physiological experiments, data analysis viz. Fourier and Hilbert transforms and attractor reconstructions, and numerical solutions of linear and nonlinear coupled oscillator models. We believe that a minimal model of coupled oscillator models that quantitatively describes the complex physiological data could be developed via such a method. Further investigations of each of these techniques will be explored in separate publications.
Developmental processes in multicellular organisms occur far from equilibrium, yet produce complex patterns with astonishing reproducibility. We measure the precision and reproducibility of bilaterally symmetric fly wings across the natural range of
genetic and environmental conditions and find that wing patterns are specified with identical spatial precision and are reproducible to within a single cell width. The early fly embryo operates at a similar degree of reproducibility, suggesting that the overall spatial precision of morphogenesis in Drosophila performs at the single cell level, arguably the physical limit of what a biological system can achieve.
Estimating early postmortem interval EPI is a difficult task in daily forensic activity due to limitations of accurate and reliable methods. The aim of the present work is to describe a novel approach in the estimation of EPI based on quantitative ma
gnetic resonance molecular imaging qMRMI using a pig phantom since post mortem degradation of pig meat is similar to that of human muscles. On a pig phantom maintained at 20 degree, using a 1.5 T MRI scanner we performed 10 scans, every 4 hours, monitoring apparent diffusion coefficient ADC, fractional anisotropy FA, magnetization transfer ration MTR, tractography and susceptibility weighted changes in muscles until 36 hours after death. Cooling of the phantom during the experiment was recorded. Histology was also obtained. Pearsons Test was carried out for statistical correlation. We found a significative statistical inverse correlation between ADC, FA, MT and PMI. Our preliminary data shows that post mortem qMRMI is a potential powerful tool in accurately determining EPI and is worth of further investigation.
We demonstrate the robust scale-invariance in the probability density function (PDF) of detrended healthy human heart rate increments, which is preserved not only in a quiescent condition, but also in a dynamic state where the mean level of heart rat
e is dramatically changing. This scale-independent and fractal structure is markedly different from the scale-dependent PDF evolution observed in a turbulent-like, cascade heart rate model. These results strongly support the view that healthy human heart rate is controlled to converge continually to a critical state.
There is much to learn through synthesis of Developmental Biology, Cognitive Science and Computational Modeling. One lesson we can learn from this perspective is that the initialization of intelligent programs cannot solely rely on manipulation of nu
merous parameters. Our path forward is to present a design for developmentally-inspired learning agents based on the Braitenberg Vehicle. Using these agents to exemplify artificial embodied intelligence, we move closer to modeling embodied experience and morphogenetic growth as components of cognitive developmental capacity. We consider various factors regarding biological and cognitive development which influence the generation of adult phenotypes and the contingency of available developmental pathways. These mechanisms produce emergent connectivity with shifting weights and adaptive network topography, thus illustrating the importance of developmental processes in training neural networks. This approach provides a blueprint for adaptive agent behavior that might result from a developmental approach: namely by exploiting critical periods or growth and acquisition, an explicitly embodied network architecture, and a distinction between the assembly of neural networks and active learning on these networks.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
