Abstract
Biomedical engineering is clearly present in modern neuroendocrinology, and indeed has come to embrace it in many respects. First, we briefly review the origins of endocrinology until neuroendocrinology, after a long saga, was established in the 1950's decade with quantified results made possible by the radioimmunoassay technique (RIA), a development contributed by the physical sciences. However, instrumentation was only one face of the quantification process, for mathematical models aiding in the study of negative feedback loops, first rather shyly and now at a growing rate, became means building the edifice of mathematical neuroendocrinology while computer assisted techniques help unravel the associated genetic aspects or the nature itself of endocrine bursts by numerical deconvolution analysis. To end the note, attention is called to the pleiotropic characteristics of neuroendocrinology, which keeps branching off almost endlessly as bioengineering does too.
Highlights
Scientific disciplines constantly evolve, usually starting at a qualitative stage, to enter later on into more quantitative stages
Its roots can be traced back to the French scientist Claude Bernard (1813-1878) with his studies on pancreas and even laying the foundations for the study of molecular signaling in endocrinology [2,3]
Several neuroendocrine glands secrete their hormones as short bursts, as well described in many papers, and such bursts can be looked at as physiological imperfect delta functions
Summary
Scientific disciplines constantly evolve, usually starting at a qualitative stage (by being mostly descriptive, as the early anatomical or zoological knowledge was), to enter later on into more quantitative stages (like counting the number of lobes of an organ). Traditional control engineering and the two previously referred to physiological applications of deconvolution analysis require the injection of a known input signal, which by and large is the impulse delta Dirac function (any other could be employed just as well, but the delta function has some advantages).
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