Evidence that minocycline treatment confounds the interpretation of neurofilament as a biomarker.

Neurofilament light (NfL) concentration in cerebrospinal fluid (CSF) and blood serves as an important biomarker in neurology drug development. Changes in NfL are generally assumed to reflect changes in neuronal damage, while little is known about the clearance of NfL from biofluids. We observed an NfL increase of 3.5-fold in plasma and 5.7-fold in CSF in an asymptomatic individual at risk for genetic prion disease following 6 weeks' treatment with oral minocycline for a dermatologic indication. Other biomarkers remained normal, and proteomic analysis of CSF revealed that the spike was exquisitely specific to neurofilaments. NfL dropped nearly to normal levels 5 weeks after minocycline cessation, and the individual remained free of disease 2 years later. Plasma NfL in dermatology patients was not elevated above normal controls. Dramatically high plasma NfL (>500 pg/mL) was variably observed in some hospitalized individuals receiving minocycline. In mice, treatment with minocycline resulted in variable increases of 1.3- to 4.0-fold in plasma NfL, with complete washout 2 weeks after cessation. In neuron-microglia co-cultures, minocycline increased NfL concentration in conditioned media by 3.0-fold without any visually obvious impact on neuronal health. We hypothesize that minocycline does not cause or exacerbate neuronal damage, but instead impacts the clearance of NfL from biofluids, a potential confounder for interpretation of this biomarker.

Enhancing cognitive control with transcranial magnetic stimulation in subject-specific frontoparietal networks.

BACKGROUND: Cognitive control processes, including those involving frontoparietal networks, are highly variable between individuals, posing challenges to basic and clinical sciences. While distinct frontoparietal networks have been associated with specific cognitive control functions such as switching, inhibition, and working memory updating functions, there have been few basic tests of the role of these networks at the individual level. METHODS: To examine the role of cognitive control at the individual level, we conducted a within-subject excitatory transcranial magnetic stimulation (TMS) study in 19 healthy individuals that targeted intrinsic ("resting") frontoparietal networks. Person-specific intrinsic networks were identified with resting state functional magnetic resonance imaging scans to determine TMS targets. The participants performed three cognitive control tasks: an adapted Navon figure-ground task (requiring set switching), n-back (working memory), and Stroop color-word (inhibition). OBJECTIVE: Hypothesis: We predicted that stimulating a network associated with externally oriented control [the "FPCN-B" (fronto-parietal control network)] would improve performance on the set switching and working memory task relative to a network associated with attention (the Dorsal Attention Network, DAN) and cranial vertex in a full within-subjects crossover design. RESULTS: We found that set switching performance was enhanced by FPCN-B stimulation along with some evidence of enhancement in the higher-demand n-back conditions. CONCLUSION: Higher task demands or proactive control might be a distinguishing role of the FPCN-B, and personalized intrinsic network targeting is feasible in TMS designs.

Evaluating and benchmarking the EEG signal quality of high-density, dry MXene-based electrode arrays against gelled Ag/AgCl electrodes.

Objective.To evaluate the signal quality of dry MXene-based electrode arrays (also termed 'MXtrodes') for electroencephalographic (EEG) recordings where gelled Ag/AgCl electrodes are a standard.Approach.We placed 4 × 4 MXtrode arrays and gelled Ag/AgCl electrodes on different scalp locations. The scalp was cleaned with alcohol and rewetted with saline before application. We recorded from both electrode types simultaneously while participants performed a vigilance task.Main results.The root mean squared amplitude of MXtrodes was slightly higher than that of Ag/AgCl electrodes (.24-1.94 uV). Most MXtrode pairs had slightly lower broadband spectral coherence (.05 to .1 dB) and Delta- and Theta-band timeseries correlation (.05 to .1 units) compared to the Ag/AgCl pair (p< .001). However, the magnitude of correlation and coherence was high across both electrode types. Beta-band timeseries correlation and spectral coherence were higher between neighboring MXtrodes in the array (.81 to .84 units) than between any other pair (.70 to .75 units). This result suggests the close spacing of the nearest MXtrodes (3 mm) more densely sampled high spatial-frequency topographies. Event-related potentials were more similar between MXtrodes (ρ⩾ .95) than equally spaced Ag/AgCl electrodes (ρ⩽ .77,p< .001). Dry MXtrode impedance (x̄= 5.15 KΩ cm2) was higher and more variable than gelled Ag/AgCl electrodes (x̄= 1.21 KΩ cm2,p< .001). EEG was also recorded on the scalp across diverse hair types.Significance.Dry MXene-based electrodes record EEG at a quality comparable to conventional gelled Ag/AgCl while requiring minimal scalp preparation and no gel. MXtrodes can record independent signals at a spatial density four times higher than conventional electrodes, including through hair, thus opening novel opportunities for research and clinical applications that could benefit from dry and higher-density configurations.

Individual-level functional connectivity predicts cognitive control efficiency.

Cognitive control (CC) is essential for problem-solving in everyday life, and CC-related deficits occur alongside costly and debilitating disorders. The tri-partite model suggests that CC comprises multiple behaviors, including switching, inhibiting, and updating. Activity within the fronto-parietal control network B (FPCN-B), the dorsal attention network (DAN), the cingulo-opercular network (CON), and the lateral default-mode network (L-DMN) is related to switching and inhibiting behaviors. However, our understanding of how these brain regions interact to bring about cognitive switching and inhibiting in individuals is unclear. In the current study, subjects performed two in-scanner tasks that required switching and inhibiting. We used support vector regression (SVR) models containing individually-estimated functional connectivity between the FPCN-B, DAN, CON and L-DMN to predict switching and inhibiting behaviors. We observed that: inter-network connectivity can predict inhibiting and switching behaviors in individuals, and the L-DMN plays a role in switching and inhibiting behaviors. Therefore, individually estimated inter-network connections are markers of CC behaviors, and CC behaviors may arise due to interactions between a set of networks.

EEG Phase Can Be Predicted with Similar Accuracy across Cognitive States after Accounting for Power and Signal-to-Noise Ratio.

EEG phase is increasingly used in cognitive neuroscience, brain-computer interfaces, and closed-loop stimulation devices. However, it is unknown how accurate EEG phase prediction is across cognitive states. We determined the EEG phase prediction accuracy of parieto-occipital alpha waves across rest and task states in 484 participants over 11 public datasets. We were able to track EEG phase accurately across various cognitive conditions and datasets, especially during periods of high instantaneous alpha power and signal-to-noise ratio (SNR). Although resting states generally have higher accuracies than task states, absolute accuracy differences were small, with most of these differences attributable to EEG power and SNR. These results suggest that experiments and technologies using EEG phase should focus more on minimizing external noise and waiting for periods of high power rather than inducing a particular cognitive state.

Alerting attention is sufficient to induce a phase-dependent behavior that can be predicted by frontal EEG.

Recent studies suggest that attention is rhythmic. Whether that rhythmicity can be explained by the phase of ongoing neural oscillations, however, is still debated. We contemplate that a step toward untangling the relationship between attention and phase stems from employing simple behavioral tasks that isolate attention from other cognitive functions (perception/decision-making) and by localized monitoring of neural activity with high spatiotemporal resolution over the brain regions associated with the attentional network. In this study, we investigated whether the phase of electroencephalography (EEG) oscillations predicts alerting attention. We isolated the alerting mechanism of attention using the Psychomotor Vigilance Task, which does not involve a perceptual component, and collected high resolution EEG using novel high-density dry EEG arrays at the frontal region of the scalp. We identified that alerting attention alone is sufficient to induce a phase-dependent modulation of behavior at EEG frequencies of 3, 6, and 8 Hz throughout the frontal region, and we quantified the phase that predicts the high and low attention states in our cohort. Our findings disambiguate the relationship between EEG phase and alerting attention.

Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia.

Aphasia is a prevalent cognitive syndrome caused by stroke. The rarity of premorbid imaging and heterogeneity of lesion obscures the links between the local effects of the lesion, global anatomic network organization, and aphasia symptoms. We applied a simulated attack approach in humans to examine the effects of 39 stroke lesions (16 females) on anatomic network topology by simulating their effects in a control sample of 36 healthy (15 females) brain networks. We focused on measures of global network organization thought to support overall brain function and resilience in the whole brain and within the left hemisphere. After removing lesion volume from the network topology measures and behavioral scores [the Western Aphasia Battery Aphasia Quotient (WAB-AQ), four behavioral factor scores obtained from a neuropsychological battery, and a factor sum], we compared the behavioral variance accounted for by simulated poststroke connectomes to that observed in the randomly permuted data. Global measures of anatomic network topology in the whole brain and left hemisphere accounted for 10% variance or more of the WAB-AQ and the lexical factor score beyond lesion volume and null permutations. Streamline networks provided more reliable point estimates than FA networks. Edge weights and network efficiency were weighted most highly in predicting the WAB-AQ for FA networks. Overall, our results suggest that global network measures provide modest statistical value beyond lesion volume when predicting overall aphasia severity, but less value in predicting specific behaviors. Variability in estimates could be induced by premorbid ability, deafferentation and diaschisis, and neuroplasticity following stroke.SIGNIFICANCE STATEMENT Poststroke, the remaining neuroanatomy maintains cognition and supports recovery. However, studies often use small, cross-sectional samples that cannot fully model the interactions between lesions and other variables that affect networks in stroke. Alternate methods are required to account for these effects. "Simulated attack" models are computational approaches that apply virtual damage to the brain and measure their putative consequences. Using a simulated attack model, we estimated how simulated damage to anatomic networks could account for language performance. Overall, our results reveal that global network measures can provide modest statistical value predicting overall aphasia severity, but less value in predicting specific behaviors. These findings suggest that more theoretically precise network models could be necessary to robustly predict individual outcomes in aphasia.

Glutamate-Weighted Magnetic Resonance Imaging (GluCEST) Detects Effects of Transcranial Magnetic Stimulation to the Motor Cortex.

Transcranial magnetic stimulation (TMS) is used in several FDA-approved treatments and, increasingly, to treat neurological disorders in off-label uses. However, the mechanism by which TMS causes physiological change is unclear, as are the origins of response variability in the general population. Ideally, objective in vivo biomarkers could shed light on these unknowns and eventually inform personalized interventions. Continuous theta-burst stimulation (cTBS) is a form of TMS observed to reduce motor evoked potentials (MEPs) for 60 min or longer post-stimulation, although the consistency of this effect and its mechanism continue to be under debate. Here, we use glutamate-weighted chemical exchange saturation transfer (gluCEST) magnetic resonance imaging (MRI) at ultra-high magnetic field (7T) to measure changes in glutamate concentration at the site of cTBS. We find that the gluCEST signal in the ipsilateral hemisphere of the brain generally decreases in response to cTBS, whereas consistent changes were not detected in the contralateral region of interest (ROI) or in subjects receiving sham stimulation.

Distrust within protected area and natural resource management: A systematic review protocol.

Trust is a key variable for successful natural resource management and is commonly the focus of conceptual and methodological development. Distrust, on the other hand, is frequently cited as an obstacle to management, but appears to be rarely defined, conceptually underdeveloped, and inconsistently examined. This systematic review protocol (OSF preregistration https://doi.org/10.17605/OSF.IO/GKUAW) was developed to answer two primary questions in relation to protected area and natural resource management: 1) How is distrust conceptualized, and 2) What methods are used to gather evidence of distrust? The aim is to provide a comprehensive overview of how distrust is theoretically developed and what questions are used to uncover distrust. Also, it will summarize findings on what leads to and results from distrust. Four academic and eight gray literature databases will be searched using Boolean keyword searches. Articles eligible for inclusion are those that present original research, gather and present evidence of distrust, and focus on protected areas and/or natural resource management. The review will result in a narrative synthesis that summarizes approaches to distrust within protected area and natural resource management.

Is there no "I" in team? Potential bias in key informant interviews when asking individuals to represent a collective perspective.

This paper sought to understand the extent to which, and how individuals use personal or collective language when asked to articulate sense of place from a collective perspective. Understanding a collective sense of place could illuminate place-based connections in natural resource industries, where it is as groups or as institutions that organizations interact with the environment rather than as individuals. While there are well known methods for collecting information about sense of place at the individual level, there is a gap in understanding the best method to collect information at a collective level. We examined the use of key-informant interviews as a method to understand collective sense of place. In Bocas del Toro, Panama, ecotourism and environmentally based organizations are becoming more prolific due to abundant natural resources, making it an interesting case study for understanding sense of place from an organizational perspective. The use of personal and collective language is examined though in-depth semi-structured interviews from 15 environmentally-oriented organizations with a total of 17 interviews. This study specifically examined whether and how key informants, when prompted to speak for their organization, spoke collectively, reflecting a collective perspective versus their own. Methods included both quantitative analysis of personal versus collective language use frequency, and qualitative examinations of how individuals used personal versus collective language. Our results indicated no difference in the frequency with which individuals use personal versus collective language. We found that how individuals situated their perspectives into an organization reflects a complex personal and collective point of view reflecting five themes of personal versus collective language use: 1) sole personal perspective, 2) sole collective perspective, 3) distinction between collective and personal perspective; 4) organization perspective with insertion of "I think"; and 5) personal and collective perspective about organization and greater community. Our research identifies a previously undiscussed potential bias of key informant interviews. These findings have implications for how researchers approach collecting information beyond the individual level.

MXene-infused bioelectronic interfaces for multiscale electrophysiology and stimulation.

Soft bioelectronic interfaces for mapping and modulating excitable networks at high resolution and at large scale can enable paradigm-shifting diagnostics, monitoring, and treatment strategies. Yet, current technologies largely rely on materials and fabrication schemes that are expensive, do not scale, and critically limit the maximum attainable resolution and coverage. Solution processing is a cost-effective manufacturing alternative, but biocompatible conductive inks matching the performance of conventional metals are lacking. Here, we introduce MXtrodes, a class of soft, high-resolution, large-scale bioelectronic interfaces enabled by Ti3C2 MXene (a two-dimensional transition metal carbide nanomaterial) and scalable solution processing. We show that the electrochemical properties of MXtrodes exceed those of conventional materials and do not require conductive gels when used in epidermal electronics. Furthermore, we validate MXtrodes in applications ranging from mapping large-scale neuromuscular networks in humans to cortical neural recording and microstimulation in swine and rodent models. Last, we demonstrate that MXtrodes are compatible with standard clinical neuroimaging modalities.

Multiplexed proteomics of autophagy-deficient murine macrophages reveals enhanced antimicrobial immunity via the oxidative stress response.

Defective autophagy is strongly associated with chronic inflammation. Loss-of-function of the core autophagy gene Atg16l1 increases risk for Crohn's disease in part by enhancing innate immunity through myeloid cells such as macrophages. However, autophagy is also recognized as a mechanism for clearance of certain intracellular pathogens. These divergent observations prompted a re-evaluation of ATG16L1 in innate antimicrobial immunity. In this study, we found that loss of Atg16l1 in myeloid cells enhanced the killing of virulent Shigella flexneri (S.flexneri), a clinically relevant enteric bacterium that resides within the cytosol by escaping from membrane-bound compartments. Quantitative multiplexed proteomics of murine bone marrow-derived macrophages revealed that ATG16L1 deficiency significantly upregulated proteins involved in the glutathione-mediated antioxidant response to compensate for elevated oxidative stress, which simultaneously promoted S.flexneri killing. Consistent with this, myeloid-specific deletion of Atg16l1 in mice accelerated bacterial clearance in vitro and in vivo. Pharmacological induction of oxidative stress through suppression of cysteine import enhanced microbial clearance by macrophages. Conversely, antioxidant treatment of macrophages permitted S.flexneri proliferation. These findings demonstrate that control of oxidative stress by ATG16L1 and autophagy regulates antimicrobial immunity against intracellular pathogens.

An insight-related neural reward signal.

Moments of insight, a phenomenon of creative cognition in which an idea suddenly emerges into awareness as an "Aha!" are often reported to be affectively positive experiences. We tested the hypothesis that problem-solving by insight is accompanied by neural reward processing. We recorded high-density EEGs while participants solved a series of anagrams. For each solution, they reported whether the answer had occurred to them as a sudden insight or whether they had derived it deliberately and incrementally (i.e., "analytically'). Afterwards, they filled out a questionnaire that measures general dispositional reward sensitivity. We computed the time-frequency representations of the EEGs for trials with insight (I) solutions and trials with analytic (A) solutions and subtracted them to obtain an I-A time-frequency representation for each electrode. Statistical Parametric Mapping (SPM) analyses tested for significant I-A and reward-sensitivity effects. SPM revealed the time, frequency, and scalp locations of several I â€‹> â€‹A effects. No A â€‹> â€‹I effect was observed. The primary neural correlate of insight was a burst of (I â€‹> â€‹A) gamma-band oscillatory activity over prefrontal cortex approximately 500 â€‹ms before participants pressed a button to indicate that they had solved the problem. We correlated the I-A time-frequency representation with reward sensitivity to discover insight-related effects that were modulated by reward sensitivity. This revealed a separate anterior prefrontal burst of gamma-band activity, approximately 100 â€‹ms after the primary I-A insight effect, which we interpreted to be an insight-related reward signal. This interpretation was supported by source reconstruction showing that this signal was generated in part by orbitofrontal cortex, a region associated with reward learning and hedonically pleasurable experiences such as food, positive social experiences, addictive drugs, and orgasm. These findings support the notion that for many people insight is rewarding. Additionally, these results may explain why many people choose to engage in insight-generating recreational and vocational activities such as solving puzzles, reading murder mysteries, creating inventions, or doing research. This insight-related reward signal may be a manifestation of an evolutionarily adaptive mechanism for the reinforcement of exploration, problem solving, and creative cognition.

Dual-process contributions to creativity in jazz improvisations: An SPM-EEG study.

Conflicting theories identify creativity either with frontal-lobe mediated (Type-2) executive control processes or (Type-1) associative processes that are disinhibited when executive control is relaxed. Musical (jazz) improvisation is an ecologically valid test-case to distinguish between these views because relatively slow, deliberate, executive-control processes should not dominate during high-quality, real-time improvisation. In the present study, jazz guitarists (n â€‹= â€‹32) improvised to novel chord sequences while 64-channel EEGs were recorded. Jazz experts rated each improvisation for creativity, technical proficiency and aesthetic appeal. Surface-Laplacian-transformed EEGs recorded during the performances were analyzed in the scalp-frequency domain using SPM12. Significant clusters of high-frequency (beta-band and gamma-band) activity were observed when higher-quality versus lower-quality improvisations were compared. Higher-quality improvisations were associated with predominantly posterior left-hemisphere activity; lower-quality improvisations were associated with right temporo-parietal and fronto-polar activity. However, after statistically controlling for experience (defined as the number of public performances previously given), performance quality was a function of right-hemisphere, largely right-frontal, activity. These results support the notion that superior creative production is associated with hypofrontality and right-hemisphere activity thereby supporting a dual-process model of creativity in which experience influences the balance between executive and associative processes. This study also highlights the idea that the functional neuroanatomy of creative production depends on whether creativity is defined in terms of the quality of products or the type of cognitive processes involved.

Full-Featured, Real-Time Database Searching Platform Enables Fast and Accurate Multiplexed Quantitative Proteomics.

Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 method's longer duty cycles. RTS with Orbiter eliminates SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiter's online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 ms. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiter's RTS quantified more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 h for RTS, 36 h for SPS-MS3).

Parallel Notched Gas-Phase Enrichment for Improved Proteome Identification and Quantification with Fast Spectral Acquisition Rates.

Gas-phase fractionation enables better quantitative accuracy, improves signal-to-noise ratios, and increases sensitivity in proteomic analyses. However, traditional gas-phase enrichment, which relies upon a large continuous bin, results in suboptimal enrichment, as most chromatographic separations are not 100% orthogonal relative to the first MS dimension (MS1m/z). As such, ions with similar m/z values tend to elute at the same retention time, which prevents the partitioning of narrow precursor m/z distributions into a few large continuous gas-phase enrichment bins. To overcome this issue, we developed and tested the use of notched isolation waveforms, which simultaneously isolate multiple discrete m/z windows in parallel (e.g., 650-700 m/z and 800-850 m/z). By comparison to a canonical gas-phase fractionation method, notched waveforms do not require bin optimization via in silico digestion or wasteful sample injections to isolate multiple precursor windows. Importantly, the collection of all m/z bins simultaneously using the isolation waveform does not suffer from the sensitivity and duty cycle pitfalls inherent to sequential collection of multiple m/z bins. Applying a notched injection waveform provided consistent enrichment of precursor ions, which resulted in improved proteome depth with greater coverage of low-abundance proteins. Finally, using a reductive dimethyl labeling approach, we show that notched isolation waveforms increase the number of quantified peptides with improved accuracy and precision across a wider dynamic range.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

Personalizing neuromodulation.

In the era of "big data", we are gaining rich person-specific information about neuroanatomy, neural function, and cognitive functions. However, the optimal ways to create precise approaches to optimize individuals' mental functions in health and disease are unclear. Multimodal analysis and modeling approaches can guide neuromodulation by combining anatomical networks, functional signal analysis, and cognitive neuroscience paradigms in single subjects. Our progress could be improved by progressing from statistical fits to mechanistic models. Using transcranial magnetic stimulation as an example, we discuss how integrating methods with a focus on mechanisms could improve our predictions TMS effects within individuals, refine our models of health and disease, and improve our treatments.

Medical Cannabis: Effects on Opioid and Benzodiazepine Requirements for Pain Control.

Background: There is currently little evidence regarding the use of medical cannabis for the treatment of intractable pain. Literature published on the subject to date has yielded mixed results concerning the efficacy of medical cannabis and has been limited by study design and regulatory issues. Objective: The objective of this study was to determine if the use of medical cannabis affects the amount of opioids and benzodiazepines used by patients on a daily basis. Methods: This single-center, retrospective cohort study evaluated opioid and benzodiazepine doses over a 6-month time period for patients certified to use medical cannabis for intractable pain. All available daily milligram morphine equivalents (MMEs) and daily diazepam equivalents (DEs) were calculated at baseline and at 3 and 6 months. Results: A total of 77 patients were included in the final analysis. There was a statistically significant decrease in median MME from baseline to 3 months (-32.5 mg; P = 0.013) and 6 months (-39.1 mg; P = 0.001). Additionally, there was a non-statistically significant decrease in median DE at 3 months (-3.75 mg; P = 0.285) and no change in median DE from baseline to 6 months (-0 mg; P = 0.833). Conclusion and Relevance: Over the course of this 6-month retrospective study, patients using medical cannabis for intractable pain experienced a significant reduction in the number of MMEs available to use for pain control. No significant difference was noted in DE from baseline. Further prospective studies are warranted to confirm or deny the opioid-sparing effects of medical cannabis when used to treat intractable pain.

Active Instrument Engagement Combined with a Real-Time Database Search for Improved Performance of Sample Multiplexing Workflows.

Quantitative proteomics employing isobaric reagents has been established as a powerful tool for biological discovery. Current workflows often utilize a dedicated quantitative spectrum to improve quantitative accuracy and precision. A consequence of this approach is a dramatic reduction in the spectral acquisition rate, which necessitates the use of additional instrument time to achieve comprehensive proteomic depth. This work assesses the performance and benefits of online and real-time spectral identification in quantitative multiplexed workflows. A Real-Time Search (RTS) algorithm was implemented to identify fragment spectra within milliseconds as they are acquired using a probabilistic score and to trigger quantitative spectra only upon confident peptide identification. The RTS-MS3 was benchmarked against standard workflows using a complex two-proteome model of interference and a targeted 10-plex comparison of kinase abundance profiles. Applying the RTS-MS3 method provided the comprehensive characterization of a 10-plex proteome in 50% less acquisition time. These data indicate that the RTS-MS3 approach provides dramatic performance improvements for quantitative multiplexed experiments.