ReviewBiomacromolecules2018
Distributions: The Importance of the Chemist's Molecular View for Biological Materials.
Review in Biomacromolecules, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 8 citations in OpenAlex.
- Supramolecular Carbohydrate Assemblies with Tunable Glycan Surfaces.Angewandte Chemie (International ed. in English) · 2026Article
- Optimizing Ligand Valency to Maximize Tendon Accumulation of Peptide-Targeted Nanoparticles.ACS applied materials & interfaces · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Characterization of materials with biological applications and assessment of physiological effects of therapeutic interventions are critical for translating research to the clinic and preventing adverse reactions. Analytical techniques typically used to characterize targeted nanomaterials and tissues rely on bulk measurement. Therefore, the resulting data represent an average structure of the sample, masking stochastic (randomly generated) distributions that are commonly present. In this Perspective, we examine almost 20 years of work our group has done in different fields to characterize and control distributions. We discuss the analytical techniques and statistical methods we use and illustrate how we leverage them in tandem with other bulk techniques. We also discuss the challenges and time investment associated with taking such a detailed view of distributions as well as the risks of not fully appreciating the extent of heterogeneity present in many systems. Through three case studies showcasing our research on conjugated polymers for drug delivery, collagen in bone, and endogenous protein nanoparticles, we discuss how identification and characterization of distributions, i.e., a molecular view of the system, was critical for understanding the observed biological effects. In all three cases, data would have been misinterpreted and insights missed if we had only relied upon spatially averaged data. Finally, we discuss how new techniques are starting to bridge the gap between bulk and molecular level analysis, bringing more opportunity and capacity to the research community to address the challenges of distributions and their roles in biology, chemistry, and the translation of science and engineering to societal challenges.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.