Despite efforts to promote diversity in the biomedical workforce, there remains a lower rate of funding of National Institutes of Health R01 applications submitted by African-American/black (AA/B) scientists relative to white scientists. To identify underlying causes of this funding gap, we analyzed six stages of the application process from 2011 to 2015 and found that disparate outcomes arise at three of the six: decision to discuss, impact score assignment, and a previously unstudied stage, topic choice. Notably, AA/B applicants tend to propose research on topics with lower award rates. These topics include research at the community and population level, as opposed to more fundamental and mechanistic investigations; the latter tend to have higher award rates. Topic choice alone accounts for over 20% of the funding gap after controlling for multiple variables, including the applicant’s prior achievements. Our findings can be used to inform interventions designed to close the funding gap.

Citation data have remained hidden behind proprietary, restrictive licensing agreements, which raises barriers to entry for analysts wishing to use the data, increases the expense of performing large-scale analyses, and reduces the robustness and reproducibility of the conclusions. For the past several years, the National Institutes of Health (NIH) Office of Portfolio Analysis (OPA) has been aggregating and enhancing citation data that can be shared publicly. Here, we describe the NIH Open Citation Collection (NIH-OCC), a public access database for biomedical research that is made freely available to the community. This dataset, which has been carefully generated from unrestricted data sources such as MedLine, PubMed Central (PMC), and CrossRef, now underlies the citation statistics delivered in the NIH iCite analytic platform. We have also included data from a machine learning pipeline that identifies, extracts, resolves, and disambiguates references from full-text articles available on the internet. Open citation links are available to the public in a major update of iCite (https://icite.od.nih.gov).

An outstanding challenge in protein folding is understanding the origin of “internal friction” in folding dynamics, experimentally identified from the dependence of folding rates on solvent viscosity. A possible origin suggested by simulation is the crossing of local torsion barriers. However, it was unclear why internal friction varied from protein to protein or for different folding barriers of the same protein. Using all-atom simulations with variable solvent viscosity, in conjunction with transition-path sampling to obtain reaction rates and analysis via Markov state models, we are able to determine the internal friction in the folding of several peptides and miniproteins. In agreement with experiment, we find that the folding events with greatest internal friction are those that mainly involve helix formation, while hairpin formation exhibits little or no evidence of friction. Via a careful analysis of folding transition paths, we show that internal friction arises when torsion angle changes are an important part of the folding mechanism near the folding free energy barrier. These results suggest an explanation for the variation of internal friction effects from protein to protein and across the energy landscape of the same protein.

In prepulse inhibition (PPI), startle responses to sudden, unexpected stimuli are markedly attenuated if immediately preceded by a weak stimulus of almost any modality. This experimental paradigm exposes a potent inhibitory process, present in nervous systems from invertebrates to humans, that is widely considered to play an important role in reducing distraction during the processing of sensory input. The neural mechanisms mediating PPI are of considerable interest given evidence linking PPI deficits with some of the cognitive disorders of schizophrenia. Here, in the marine mollusk Tritonia diomedea, we describe a detailed cellular mechanism for PPI--a combination of presynaptic inhibition of startle afferent neurons together with distributed postsynaptic inhibition of several downstream interneuronal sites in the startle circuit.

A programmable ligand display system can be used to dissect the multivalent effects of ligand binding to a membrane receptor. An antagonist of the A2A adenosine receptor, a G-protein-coupled receptor that is a drug target for neurodegenerative conditions, was displayed in 35 different multivalent configurations, and binding to A2A was determined. A theoretical model based on statistical mechanics was developed to interpret the binding data, suggesting the importance of receptor dimers. Using this model, extended multivalent arrangements of ligands were constructed with progressive improvements in binding to A2A. The results highlight the ability to use a highly controllable multivalent approach to determine optimal ligand valency and spacing that can be subsequently optimized for binding to a membrane receptor. Models explaining the multivalent binding data are also presented.

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SYNOPSIS. Two groups of interneurons, Tr1 and DRI, have been identified in the escape swim circuit of the marine mollusc Tritonia diomedea that have important roles in behavioral initiation. DRI functions as a command neuron, receiving direct excitatory input from the afferent neurons, and in turn directly exciting the DSI neurons of the central pattern generator. DRI fires throughout the swim motor program, and activity in DRI is both necessary and sufficient for sensory input to elicit the swim motor program. Tr1 is an excitatory interneuron that fires briefly in response to sensory input and then remains silent during the motor program. Tr1 excites DRI with an excitatory connection that has fast and slow components and thus appears to have a role in converting brief afferent neuron activity to long-lasting firing in downstream circuit elements. These neurons complete the description of a continuous synaptic pathway from afferent to flexion neurons in the Tritonia swim circuit. Their identification should facilitate studies of motor program initiation, as well as of how various forms of experience, including simple forms of learning, act to influence neuronal decision-making processes.

In order to better understand how nonspecific interactions between solutes can modulate specific biochemical reactions taking place in complex media, we introduce a simplified model aimed at elucidating general principles. In this model, solutions containing two or three species of interacting globular proteins are modeled as a fluid of spherical particles interacting through square well potentials that qualitatively capture both steric hard core repulsion and longer-ranged attraction or repulsion. The excess chemical potential, or free energy of solvation, of each particle species is calculated as a function of species concentrations, particle radii, and square well interaction range and depth. The results of analytical models incorporating two-body and three-body interactions are compared with the estimates of free energy obtained via Widom insertion into simulated equilibrium square-well fluids. The analytical models agree well with results of numeric simulations carried out for a variety of model parameters and fluid compositions up to a total particle volume fraction of ca. 0.2.