Odd E. Hanssen and the Hanssen method for measurement of single-nephron glomerular filtration rate
Bibliographic record
Abstract
In the middle of the twentieth century, the suspicion that deep and superficial nephrons might serve different functions created a demand for measurement of single-nephron glomerular filtration rate (SNGFR). Rather unexpectedly, the answer came from Odd E. Hanssen (1917-1964), a Norwegian physician working on his own in the Department of Pathological Anatomy, University of Oslo, with minimal support and no interaction with renal physiologists. In 1963, after nearly 10 years of work, he presented the ferrocyanide method, allowing simultaneous estimates of SNGFR in a large number of nephrons in all layers of the kidney. This review first describes his early visions of the method and the elaborate and extremely time-consuming studies in mice to verify the technique. As a byproduct came valuable information on the relationship between nephron size and SNGFR, glomerular intermittency, and the emptying of the tubules on filtration stop. Hanssen died from a cerebral hemorrhage in 1964, and for several years the method seemed entirely forgotten. Fortunately, Andrew Baines took up the use of ferrocyanide in 1963-1964 while working on his thesis in Toronto, but his first publication came in 1969 from Saclay, France, in collaboration with Christian de Rouffignac. Modifications allowing determination of absolute SNGFR were worked out by de Rouffignac and by Jaime Coehlo in New York. Thereafter, the "Hanssen method" spread rapidly, and in the early 1980s about 50 reports had been published from 17 laboratories in 9 countries. The distribution of SNGFR in mammals, birds, and fish was described, as well as the response to water and salt loads, vasoactive substances, hormones, varying perfusion pressure, blood loss, etc. Finally, after mentioning two recent methods inspired by the Hanssen technique but using other filtration markers, the review concludes that most of our present knowledge on SNGFR distribution and regulation has been obtained by the method developed by Hanssen 40 years ago.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".