Measuring the impact of scientific publications and publication extenders: examples of novel approaches.

Different stakeholders, such as authors, research institutions, and healthcare professionals (HCPs) may determine the impact of peer-reviewed publications in different ways. Commonly-used measures of research impact, such as the Journal Impact Factor or the H-index, are not designed to evaluate the impact of individual articles. They are heavily dependent on citations, and therefore only measure impact of the overall journal or researcher respectively, taking months or years to accrue. The past decade has seen the development of article-level metrics (ALMs), that measure the online attention received by an individual publication in contexts including social media platforms, news media, citation activity, and policy and patent citations. These new tools can complement traditional bibliometric data and provide a more holistic evaluation of the impact of a publication. This commentary discusses the need for ALMs, and summarizes several examples - PlumX Metrics, Altmetric, the Better Article Metrics score, the EMPIRE Index, and scite. We also discuss how metrics may be used to evaluate the value of "publication extenders" - educational microcontent such as animations, videos and plain-language summaries that are often hosted on HCP education platforms. Publication extenders adapt a publication's key data to audience needs and thereby extend a publication's reach. These new approaches have the potential to address the limitations of traditional metrics, but the diversity of new metrics requires that users have a keen understanding of which forms of impact are relevant to a specific publication and select and monitor ALMs accordingly.

Different readers have different ways of deciding how important scientific articles are. The usual methods used to measure the impact of research, like the Journal Impact Factor or the H-index, are not meant to measure this for individual articles. These methods mainly look at how many times the articles are mentioned by others, and it can take a long time to see the impact.But in the past ten years, new tools called article-level metrics (ALMs) have been created. These tools measure how much attention an article gets online, like on social media, in the news, or when other researchers talk about it. ALMs are better at explaining how important a specific article is. They can work together with the usual methods to measure impact.This paper talks about why ALMs are important and gives examples of these tools, like PlumX Metrics, Altmetric, the Better Article Metrics score, the EMPIRE Index, and scite. It also explains how these tools can help us see the value of animations, videos, or summaries in simple language. These make it easier for more people to understand and learn from the articles.These new ways of measuring impact can help us see how important articles are in a more complete way. But because there are many different ways to measure this, it's important for users to understand which methods are relevant for a specific article and keep track of them.

A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement.

Low-intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation, applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional MRI (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability. Despite the growing number of published reports, there are no consensus-based checklists for disclosing methodological details of concurrent tES-fMRI studies. The objective of this work was to develop a consensus-based checklist of reporting standards for concurrent tES-fMRI studies to support methodological rigor, transparency and reproducibility (ContES checklist). A two-phase Delphi consensus process was conducted by a steering committee (SC) of 13 members and 49 expert panelists through the International Network of the tES-fMRI Consortium. The process began with a circulation of a preliminary checklist of essential items and additional recommendations, developed by the SC on the basis of a systematic review of 57 concurrent tES-fMRI studies. Contributors were then invited to suggest revisions or additions to the initial checklist. After the revision phase, contributors rated the importance of the 17 essential items and 42 additional recommendations in the final checklist. The state of methodological transparency within the 57 reviewed concurrent tES-fMRI studies was then assessed by using the checklist. Experts refined the checklist through the revision and rating phases, leading to a checklist with three categories of essential items and additional recommendations: (i) technological factors, (ii) safety and noise tests and (iii) methodological factors. The level of reporting of checklist items varied among the 57 concurrent tES-fMRI papers, ranging from 24% to 76%. On average, 53% of checklist items were reported in a given article. In conclusion, use of the ContES checklist is expected to enhance the methodological reporting quality of future concurrent tES-fMRI studies and increase methodological transparency and reproducibility.

Effects of Transcranial Direct Current Stimulation on Baseline and Slope of Prefrontal Cortex Hemodynamics During a Spatial Working Memory Task.

Background: Transcranial direct current stimulation (tDCS) has been shown to be an inexpensive, safe, and effective way of augmenting a variety of cognitive abilities. Relatively recent advances in neuroimaging technology have provided the ability to measure brain activity concurrently during active brain stimulation rather than after stimulation. The effects on brain activity elicited by tDCS during active tDCS reported by initial studies have been somewhat conflicted and seemingly dependent on whether a behavioral improvement was observed. Objective: The current study set out to address questions regarding behavioral change, within and between-participant designs as well as differentiating the effects on hemodynamic amplitude and baseline during active tDCS stimulation. Methods: We tested the effects of transcranial direct current stimulation (tDCS) on anterior hemodynamics in prefrontal cortex during performance on a spatial memory task. Prefrontal cortex activity was measured with functional near infrared spectroscopy (fNIRS), a wearable and portable neuroimaging technique that utilizes near infrared light to measure cortical oxygenated and deoxygenated hemoglobin changes non-invasively. There were two groups, one group (n = 10) received only sham stimulation and the other group (n = 11) received sham followed by anodal stimulation to right ventral lateral prefrontal cortex. Results: Analyses revealed an increase in spatial memory performance following tDCS stimulation. This augmented performance was accompanied by changes to oxygenation (HbO-HbR) at the onset of the hemodynamic response in bilateral dorsolateral prefrontal cortex and left ventral medial prefrontal cortex. In these regions we also observed that stimulation improved neural processing efficiency, by reducing oxygenation and increasing performance from block to block. During and following tDCS stimulation, it was also observed that in bilateral dorsolateral prefrontal cortex the relationship between performance and oxygenation inverted, from a negative relationship to a positive relationship. Conclusion: The results suggest that tDCS is predominately a mechanism for changing neurons propensity for activity as opposed to their strength of activity. tDCS not only alters the efficiency of task relevant processing, but also the nature in which hemodynamic resources are used during augmented task performance.

Theories and Methods for Labeling Cognitive Workload: Classification and Transfer Learning.

There are a number of key data-centric questions that must be answered when developing classifiers for operator functional states. "Should a supervised or unsupervised learning approach be used? What degree of labeling and transformation must be performed on the data? What are the trade-offs between algorithm flexibility and model interpretability, as generally these features are at odds?" Here, we focus exclusively on the labeling of cognitive load data for supervised learning. We explored three methods of labeling cognitive states for three-state classification. The first method labels states derived from a tertiary split of trial difficulty during a spatial memory task. The second method was more adaptive; it employed a mixed-effects stress-strain curve and estimated an individual's performance asymptotes with respect to the same spatial memory task. The final method was similar to the second approach; however, it employed a mixed-effects Rasch model to estimate individual capacity limits within the context of item response theory for the spatial memory task. To assess the strength of each of these labeling approaches, we compared the area under the curve (AUC) for receiver operating curves (ROCs) from elastic net and random forest classifiers. We chose these classifiers based on a combination of interpretability, flexibility, and past modeling success. We tested these techniques across two groups of individuals and two tasks to test the effects of different labeling techniques on cross-person and cross-task transfer. Overall, we observed that the Rasch model labeling paired with a random forest classifier led to the best model fits and showed evidence of both cross-person and cross-task transfer.

Individual differences in learning correlate with modulation of brain activity induced by transcranial direct current stimulation.

Transcranial direct current stimulation (tDCS) has been shown to enhance cognitive performance on a variety of tasks. It is hypothesized that tDCS enhances performance by affecting task related cortical excitability changes in networks underlying or connected to the site of stimulation facilitating long term potentiation. However, many recent studies have called into question the reliability and efficacy of tDCS to induce modulatory changes in brain activity. In this study, our goal is to investigate the individual differences in tDCS induced modulatory effects on brain activity related to the degree of enhancement in performance, providing insight into this lack of reliability. In accomplishing this goal, we used functional magnetic resonance imaging (fMRI) concurrently with tDCS stimulation (1 mA, 30 minutes duration) using a visual search task simulating real world conditions. The experiment consisted of three fMRI sessions: pre-training (no performance feedback), training (performance feedback which included response accuracy and target location and either real tDCS or sham stimulation given), and post-training (no performance feedback). The right posterior parietal cortex was selected as the site of anodal tDCS based on its known role in visual search and spatial attention processing. Our results identified a region in the right precentral gyrus, known to be involved with visual spatial attention and orienting, that showed tDCS induced task related changes in cortical excitability that were associated with individual differences in improved performance. This same region showed greater activity during the training session for target feedback of incorrect (target-error feedback) over correct trials for the tDCS stim over sham group indicating greater attention to target features during training feedback when trials were incorrect. These results give important insight into the nature of neural excitability induced by tDCS as it relates to variability in individual differences in improved performance shedding some light the apparent lack of reliability found in tDCS research.

Simultaneous tDCS-fMRI Identifies Resting State Networks Correlated with Visual Search Enhancement.

This study uses simultaneous transcranial direct current stimulation (tDCS) and functional MRI (fMRI) to investigate tDCS modulation of resting state activity and connectivity that underlies enhancement in behavioral performance. The experiment consisted of three sessions within the fMRI scanner in which participants conducted a visual search task: Session 1: Pre-training (no performance feedback), Session 2: Training (performance feedback given), Session 3: Post-training (no performance feedback). Resting state activity was recorded during the last 5 min of each session. During the 2nd session one group of participants underwent 1 mA tDCS stimulation and another underwent sham stimulation over the right posterior parietal cortex. Resting state spontaneous activity, as measured by fractional amplitude of low frequency fluctuations (fALFF), for session 2 showed significant differences between the tDCS stim and sham groups in the precuneus. Resting state functional connectivity from the precuneus to the substantia nigra, a subcortical dopaminergic region, was found to correlate with future improvement in visual search task performance for the stim over the sham group during active stimulation in session 2. The after-effect of stimulation on resting state functional connectivity was measured following a post-training experimental session (session 3). The left cerebellum Lobule VIIa Crus I showed performance related enhancement in resting state functional connectivity for the tDCS stim over the sham group. The ability to determine the relationship that the relative strength of resting state functional connectivity for an individual undergoing tDCS has on future enhancement in behavioral performance has wide ranging implications for neuroergonomic as well as therapeutic, and rehabilitative applications.

Transcranial direct current stimulation augments perceptual sensitivity and 24-hour retention in a complex threat detection task.

We have previously shown that transcranial direct current stimulation (tDCS) improved performance of a complex visual perceptual learning task (Clark et al. 2012). However, it is not known whether tDCS can enhance perceptual sensitivity independently of non-specific, arousal-linked changes in response bias, nor whether any such sensitivity benefit can be retained over time. We examined the influence of stimulation of the right inferior frontal cortex using tDCS on perceptual learning and retention in 37 healthy participants, using signal detection theory to distinguish effects on perceptual sensitivity (d') from response bias (ß). Anodal stimulation with 2 mA increased d', compared to a 0.1 mA sham stimulation control, with no effect on ß. On completion of training, participants in the active stimulation group had more than double the perceptual sensitivity of the control group. Furthermore, the performance enhancement was maintained for 24 hours. The results show that tDCS augments both skill acquisition and retention in a complex detection task and that the benefits are rooted in an improvement in sensitivity (d'), rather than changes in response bias (ß). Stimulation-driven acceleration of learning and its retention over 24 hours may result from increased activation of prefrontal cortical regions that provide top-down attentional control signals to object recognition areas.

Chemical conditionality: a genetic strategy to probe organelle assembly.

The assembly of the Escherichia coli outer membrane (OM) is poorly understood. Although insight into fundamental cellular processes is often obtained from studying mutants, OM-defective mutants have not been very informative because they generally have nonspecific permeability defects. Here we show that toxic small molecules can be used in selections employing strains with permeability defects to create particular chemical conditions that demand specific suppressor mutations. Suppressor phenotypes are correlated with the physical properties of the small molecules, but the mutations are not in their target genes. Instead, mutations allow survival by partially restoring membrane impermeability. Using "chemical conditionality," we identified mutations in yfgL, and, here and in the accompanying paper by Wu et al. published in this issue of Cell (Wu et al., 2005), we show that YfgL is part of a multiprotein complex involved in the assembly of OM beta barrel proteins. We posit that panels of toxic small molecules will be useful for generating chemical conditionalities that enable identification of genes required for organelle assembly in other organisms.

Differential inhibition of Staphylococcus aureus PBP2 by glycopeptide antibiotics.

The glycopeptide antibiotics prevent maturation of the bacterial cell wall by binding to the terminal d-alanyl-d-alanine moiety of peptidoglycan precursors, thereby inhibiting the enzymes involved in the final stages of peptidoglycan synthesis. However, there are significant differences in the biological activity of particular glycopeptide derivatives that are not related to their affinity for d-Ala-d-Ala. We compare the ability of vancomycin and a set of clinically relevant glycopeptides to inhibit Staphylococcus aureus PBP2 (penicillin binding protein), the major transglycosylase in a clinically relevant pathogen, S. aureus. We report experiments suggesting that activity differences between glycopeptides against this organism reflect a combination of substrate binding and secondary interactions with key enzymes involved in peptidoglycan synthesis.

Crystal structure of the MurG:UDP-GlcNAc complex reveals common structural principles of a superfamily of glycosyltransferases.

MurG is an essential glycosyltransferase that forms the glycosidic linkage between N-acetyl muramyl pentapeptide and N-acetyl glucosamine in the biosynthesis of the bacterial cell wall. This enzyme is a member of a major superfamily of NDP-glycosyltransferases for which no x-ray structures containing intact substrates have been reported. Here we present the 2.5-A crystal structure of Escherichia coli MurG in complex with its donor substrate, UDP-GlcNAc. Combined with genomic analysis of other superfamily members and site-specific mutagenesis of E. coli MurG, this structure sheds light on the molecular basis for both donor and acceptor selectivity for the superfamily. This structural analysis suggests that it will be possible to evolve new glycosyltransferases from prototypical superfamily members by varying two key loops while maintaining the overall architecture of the family and preserving key residues.