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Biomedical subjects

M Lampl

Publications and source records attributed to M Lampl.

23 records · Page 2Linked to original sources
PubMedDate not supplied

Further observations on diurnal variation in standing height.

A total of 328 daily assessments of standing height were made on one boy between the ages of 12.83 and 13.95 years; 292 of these were replicates to establish reliability of measurement. On 300 days, measurements were taken in the morning within 1/2 h of rising (which varied between 0700 and 1100 h) and repeated before bed on the same day, between 2100 and 2300 h. The standard error of measurement from 292 duplicate measurements was 0.12 cm. A mean of 0.98 +/- 0.2 cm decrease in stature occurred during the course of the day. A similar decrease was found on three occasions after 2-3 h naps.

Adolescent↗
PubMedDate not supplied

A case study of daily growth during adolescence: a single spurt or changes in the dynamics of saltatory growth?

Standing height of one adolescent male was measured daily between the ages of 12.83 and 13.95 years on 328 days out of 389 consecutive days according to standard techniques for maximal stature measurement. The serial growth data were analysed by a modification of techniques developed to identify patterns in serial hormone data. The entire growth in height during this interval occurred during 12 non-periodic saltatory episodes with amplitude of 0.92 +/- 0.09 cm (SEM) in < or = 24 h separated by 3-100 days of no significant growth. The proposition that adolescent growth is characterized by a change in the dynamics of growth saltus amplitude and/or frequency is suggested.

Adolescent↗
PubMedDate not supplied

Wrinkles induced by the use of smoothing procedures applied to serial growth data.

This paper elucidates the effects of moving average filters when applied to serial growth measurements. This is a question of interest because smoothing procedures are inherently part of a number of analytical methods presently employed in auxological analyses. Particular attention is paid to sequential growth data analysed to identify what has been described as pulsatile, saltation and stasis patterns or mini-growth spurts. When applied to pulsatile, or saltatory, time series data the process of smoothing itself creates artifactual temporal patterns in the time series data similar to previously described mini growth spurts while removing the actual pulsatile characteristics of the data. These observations illustrate that smoothing approaches add noise to time series data while removing meaningful patterns in the original data sequence. Analyses employing such approaches produce results that include waveforms or other fluctuations compatible with an underlying pulsatile driving mechanism, but do not necessarily reflect the temporal characteristics of the original biological process.

Biometry↗
PubMedDate not supplied

An example of variation and pattern in saltation and stasis growth dynamics.

The serial data from two siblings, aged 6.6 and 7.5 years of age at the initiation of the study, measured each evening for total standing height during 365 days, are analysed by two methods to investigate the nature of the underlying growth pattern. The saltation and stasis model, designed to identify the presence of statistically significant pulses in sequential data, is compared for goodness-of-fit to first to sixth degree polynomial functions, used to investigate the presence of a slowly varying smooth continuous function in the data, and high order polynomials of the same degree of flexibility as the individual's saltation and stasis results. The saltation and stasis model is found to better-fit the experimental data than the slowly varying smooth continuous functions (p < 0.01 to 0.001). The timing characteristics of the saltation and stasis patterns are investigated and the temporal patterns are suggestive of a non-random, aperiodical deterministic system.

Algorithms↗