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Nephrin is a key functional component of the slit diaphragm, the structurally unresolved molecular filter in renal glomerular capillaries. Abnormal nephrin or its absence results in severe proteinuria and loss of the slit diaphragm. The diaphragm is a thin extracellular membrane spanning the approximately 40-nm-wide filtration slit between podocyte foot processes covering the capillary surface. Using electron tomography, we show that the slit diaphragm comprises a network of winding molecular strands with pores the same size as or smaller than albumin molecules, as demonstrated in humans, rats, and mice. In the network, which is occasionally stratified, immunogold-nephrin antibodies labeled individually detectable globular cross strands, about 35 nm in length, lining the lateral elongated pores. The cross strands, emanating from both sides of the slit, contacted at the slit center but had free distal endings. Shorter strands associated with the cross strands were observed at their base. Immunolabeling of recombinant nephrin molecules on transfected cells and in vitrified solution corroborated the findings in kidney. Nephrin-deficient proteinuric patients with Finnish-type congenital nephrosis and nephrin-knockout mice had only narrow filtration slits that lacked the slit diaphragm network and the 35-nm-long strands but contained shorter molecular structures. The results suggest the direct involvement of nephrin molecules in constituting the macromolecule-retaining slit diaphragm and its pores.

This paper contributes to a critical methodological discussion that has direct ramifications for policy studies: how computational methods can be concretely incorporated into existing processes of textual analysis and interpretation without compromising scientific integrity. We focus on the computational method of topic modeling and investigate how it interacts with two larger families of qualitative methods: content and classification methods characterized by interest in words as communication units and discourse and representation methods characterized by interest in the meaning of communicative acts. Based on analysis of recent academic publications that have used topic modeling for textual analysis, our findings show that different mixed-method research designs are appropriate when combining topic modeling with the two groups of methods. Our main concluding argument is that topic modeling enables scholars to apply policy theories and concepts to much larger sets of data. That said, the use of computational methods requires genuine understanding of these techniques to obtain substantially meaningful results. We encourage policy scholars to reflect carefully on methodological issues, and offer a simple heuristic to help identify and address critical points when designing a study using topic modeling.

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