High-Throughput Covalent Modifier Screening with Acoustic Ejection Mass Spectrometry.

Interests in covalent drugs have grown in modern drug discovery as they could tackle challenging targets traditionally considered "undruggable". The identification of covalent binders to target proteins typically involves directly measuring protein covalent modifications using high-resolution mass spectrometry. With a continually expanding library of compounds, conventional mass spectrometry platforms such as LC-MS and SPE-MS have become limiting factors for high-throughput screening. Here, we introduce a prototype high-resolution acoustic ejection mass spectrometry (AEMS) system for the rapid screening of a covalent modifier library comprising ∼10,000 compounds against a 50 kDa-sized target protein─Werner syndrome helicase. The screening samples were arranged in a 1536-well format. The sample buffer containing high-concentration salts was directly analyzed without any cleanup steps, minimizing sample preparation efforts and ensuring protein stability. The entire AEMS analysis process could be completed within a mere 17 h. An automated data analysis tool facilitated batch processing of the sample data and quantitation of the formation of various covalent protein-ligand adducts. The screening results displayed a high degree of fidelity, with a Z' factor of 0.8 and a hit rate of 2.3%. The identified hits underwent orthogonal testing in a biochemical activity assay, revealing that 75% were functional antagonists of the target protein. Notably, a comparative analysis with LC-MS showcased the AEMS platform's low risk of false positives or false negatives. This innovative platform has enabled robust high-throughput covalent modifier screening, featuring a 10-fold increase in library size and a 10- to 100-fold increase in throughput when compared with similar reports in the existing literature.

Exploring the relationship between manual dexterity and cognition in people with multiple sclerosis: 9-hole peg and multiple cognitive functions.

AIM AND RATIONALE: Problems with manual dexterity and cognition impact the everyday performance of people with multiple sclerosis (PwMS). Accumulated findings point to the relationship between deficits in manual dexterity and auditory domains of cognition with a lack of evidence on visuospatial and verbal aspects of cognitive functioning. Therefore, this study explores the relationship between manual dexterity and cognition in a cohort of PwMS. METHOD: This cross-sectional study collected data from 63 PwMS aged 22 to 55 through a convenient sampling method. Participants were diagnosed with relapsing-remitting multiple sclerosis (RRMS). Cognition was measured using a multi-domain computerized cognitive testing, NeuroTrax, and manual dexterity was measured using a 9-hole peg assessment. Spearman correlation was used to identify the correlation among cognition subtests as well as with manual dexterity. Linear regression analysis was also conducted to identify whether manual dexterity predicts cognitive functioning. RESULTS: A significant negative correlation was found between 9-hole peg scores and global cognitive scores (GCS), r = -0.34, p = 006. The manual dexterity scores were also shown to predict GCS, R2= 0.165, p = 0.001. CONCLUSION: Manual dexterity was found to not only predict cognitive dysfunction but was also associated with multiple cognitive domains. Understanding the relationship between manual dexterity and cognition and the inferred progression of deficits can assist clinicians to provide interventions at earlier stages of disease progression to potentially increase daily functioning and quality of life (QoL).

High-Throughput Compound Quality Assessment with High-Mass-Resolution Acoustic Ejection Mass Spectrometry: An Automatic Data Processing Toolkit.

Pharmacological screening heavily relies on the reliability of compound libraries. To ensure the accuracy of screening results, fast and reliable quality control (QC) of these libraries is essential. While liquid chromatography (LC) with ultraviolet (UV) or mass spectrometry (MS) detection has been employed for molecule QC on small sample sets, the analytical throughput becomes a bottleneck when dealing with large libraries. Acoustic ejection mass spectrometry (AEMS) is a high-throughput analytical platform that covers a broad range of chemical structural space. In this study, we present the utilization of an AEMS system equipped with a high-resolution MS analyzer for high-throughput compound QC. To facilitate efficient data processing, which is a key challenge for such a high-throughput application, we introduce an automatic data processing toolkit that allows for the high-throughput assessment of the sample standards' quantitative and qualitative characteristics, including purity calculation with the background processing option. Moreover, the toolkit includes a module for quantitatively comparing spectral similarity with the reference library. Integrating the described high-resolution AEMS system with the data processing toolkit effectively eliminates the analytical bottleneck, enabling a rapid and reliable compound quality assessment of large-scale compound libraries.

Multiple Sclerosis, Fatigue, Expanded Disability Status Scale: A Cross-Sectional Exploration of Sleep Efficiency and Quantitative Sleep Parameters.

BACKGROUND: Poor sleep quality and sleep disorders are more prevalent in individuals with multiple sclerosis (MS) than in the general population. Poor sleep has been correlated with worse MS outcomes. Sleep efficiency (SE) is one of the most sensitive markers of sleep quality. There is very little written about SE and other polysomnography (PSG) parameters and MS measures. METHODS: This is a retrospective review of 280 consecutive individuals with MS evaluated by PSGs and other standardized MS measures over 13 years at a comprehensive MS center. In addition, the cohort was assessed with 2 fatigue scales, the Epworth Sleepiness Scale, and the Expanded Disability Status Scale. A comparison of means test (independent t test) and a correlation coefficient (r) were used. RESULTS: The PSG measures of SE and Total Sleep Time were significantly different between a group of individuals with MS with a disease duration of more than 5 years vs a group of individuals with MS with a disease duration less than or equal to 5 years. Prevalence of obstructive sleep apnea was 63%, higher than reported in the literature while the prevalence of moderate to severe obstructive sleep apnea was 33.4%, which was lower than reported. CONCLUSIONS: Longer disease duration and worse disability correlate with sleep quality as measured by SE.

SpectraX: A Straightforward Tool for Principal Component Analysis-Based Spectral Analysis.

The analysis of complex spectra is an important component of direct/ambient mass spectrometry (MS) applications such as natural product screening. Unlike chromatography-based metabolomics or proteomics approaches, which rely on software and algorithms, the work of spectral screening is mostly performed manually in the initial stages of research and relies heavily on the experience of the analyst. As a result, throughput and spectral screening reliability are problematic when dealing with large amounts of data. Here, we present SpectraX, a MATLAB-based application, which can analyze MS spectra and quickly locate m/z features from them. Principal component analysis (PCA) is used to analyze the data set, and scoring plots are presented to help in understanding the clustering of data. The algorithm uses mass to charge (m/z) features to produce a list of potential natural products.

Peering further into the mind's eye: combining visual evoked potential and optical coherence tomography measures enhances insight into the variance in cognitive functioning in multiple sclerosis.

BACKGROUND: Spectral Optical Coherence Tomography (OCT) and Visual Evoked Potentials (VEPs) have both emerged as potentially useful biomarkers of cognitive decline in people with multiple sclerosis (PwMS). Their combined use may provide additional predictive value for identifying disease impact, progression, and remyelination capacity above-and-beyond what is captured using either approach alone. OBJECTIVE: We examined the relationship between OCT/VEP measures and cognitive functioning in 205 PwMS. OCT measures included Retinal Nerve Fiber Layer Volume (RNFLV), Papillo-Macular Bundle Volume (PBMV), and Macular Volume (MV). VEP measures included latency of the P100, and inter-ocular latency. Cognitive performance was evaluated across seven separate domains of performance, and for overall cognition, using the NeuroTrax computerized testing battery. RESULTS: Both OCT and VEP measures were significantly correlated with cognitive performance across several domains. Linear regression models that controlled for the influence of visual acuity revealed (1) that reduced MV was significantly predictive of poorer visual-spatial functioning, and (2) that delayed VEP latency was significantly predictive of performance in global cognitive functioning and visual-spatial functioning, after controlling for multiple comparisons. Among PwMS with normal visual acuity, PwMS with a combination of both relatively low MV and delayed VEP latency tended to have poorer performance in the domains of global, executive, and visual-spatial functioning compared to PwMS with both high MV and normal VEP latency. CONCLUSION: Approaches that combine the use of OCT and VEP measures can enhance insight into underlying factors that contribute to variance in cognitive functioning in PwMS.

Auditory Test of Processing Speed: Preliminary validation of a smartphone-based test of mental speed.

BACKGROUND: The Symbol Digit Modalities Test (SDMT) is a gold-standard measure of cognitive efficiency and processing speed for people with multiple sclerosis (PwMS) but relies on vision and oculomotor function. OBJECTIVES: To develop and validate a new processing speed test with minimal memory involvement and no eye function requirements. METHODS: We created an Auditory Test of Processing Speed (ATOPS). A total of 122 PwMS, of whom 33 were severely disabled (median Expanded Disability Status Scale 8.0) and 37 healthy volunteers (HVs), were enrolled. We assessed sensitivity to discriminate MS participants from HVs, convergent validity between ATOPS and SDMT, sensitivity to discriminate between cognitively impaired (CI) and cognitively preserved (CP) MS participants, and correlations with MS pathology (overall brain lesion burden). Acceptability was examined with completion rates and participant ratings of ATOPS. RESULTS: ATOPS discriminated PwMS from HVs (d = 0.739-0.856), correlated with SDMT (|r| = 0.528-0.587), discriminated between CI and CP PwMS (d = 0.623-0.776), and correlated with lesion burden (r = 0.332-0.436). All groups indicated high favorability of ATOPS and severely disabled MS patients could be assessed by ATOPS more frequently than by SDMT (100% vs. 72.4% completion). CONCLUSIONS: ATOPS is a novel, accessible, and acceptable cognitive processing speed test that may be useful in clinical and/or research settings.

Multiple sclerosis and quality of life: The role of cognitive impairment on quality of life in people with multiple sclerosis.

BACKGROUND: Multiple Sclerosis (MS), a chronic disease of the central nervous system (CNS), affects functional ability and quality of life (QoL). Depression, fatigue, and disability status are among the many factors that have been shown to impact QoL in people with MS, but the extent to which MS-related cognitive impairment is related to QoL is understudied in the literature. OBJECTIVE: The purpose of this study was to determine relevant predictors of QoL from a wide list of symptoms including physical disability, and a multi-dimensional computerized cognitive assessment battery (CAB), depression, fatigue, and demographic variables (including employment status). In addition, the unique predictive power of cognitive impairment on QoL was explored in relation to other common factors of disease impact. METHODS: 171 people with MS (PwMS) were evaluated with a computerized assessment battery (CAB), EDSS examination, and validated Patient Reported Outcome (PRO) measures (Multiple Sclerosis Impact Scale, MSIS-29; Beck Depression Inventory - Second Edition BDI-2; and the Modified Fatigue Impact Scale, MFIS). RESULTS: 171 PwMS were included [Age: 46.02 years ± 9.85, 124 (72.5%) female]. Depression and fatigue scores were highly correlated with MSIS-29. EDSS, unemployment, memory, executive functioning, and motor skills were moderately correlated with MSIS-29. Predictors of QoL were EDSS, depression, fatigue, executive functioning, and attention. Attention and executive functioning were predictive of QoL even after controlling for demographic variables, fatigue, depression, and physical disability status. CONCLUSION: Findings indicate the need for comprehensive and quantified evaluation of all factors associated with disease burden, which will ultimately serve to improve the QoL in PwMS through more targeted and patient-centered care.

Cognitive impairment, fatigue and depression in multiple sclerosis: Is there a difference between benign and non-benign MS?

INTRODUCTION: Multiple Sclerosis (MS) is a chronic inflammatory and degenerative disease of the central nervous system (CNS). The severity of disability in people with MS (PwMS) is generally measured with the Expanded Disability Status Scale (EDSS). A variant of MS known as 'benign MS' (BMS) has been defined as an EDSS score of 3 or lower, combined with a disease duration of 10 years or longer; however, there is disagreement in the field about whether BMS really exists. Given that the EDSS does not capture cognitive issues, communication dysfunction, fatigue, depression, or anxiety properly, its ability to accurately represent disability in all PwMS, including BMS, remains questionable. METHODS: In this study, 141 persons with BMS (PwBMS) were included, consisting of 115 females (82%) and 26 males (18%) with a mean age of 50.8 (±8.68). A computerized test battery (NeuroTrax®) was used to assess cognition, covering seven cognitive domains (memory, executive function, visual-spatial processing, verbal function, attention, information processing, and motor skills). Fatigue was measured using the Fatigue Severity Scale (FSS). The Beck Depression Inventory (BDI) was used to assess symptoms of depression. Cognitive impairment was defined for this study as when someone has a score lower than 85 in at least two subdomains of the cognitive test battery. Rates of impairment were compared to 158 persons with non-benign MS (PwNBMS; with a disease duration of 10 years and longer and an EDSS score higher than 3) and 487 PwMS with a disease duration of fewer than 10 years. RESULTS: Cognitive impairment was found in 38% of PwBMS and in 66% of PwNBMS (p<0.001). In PwBMS, the lowest rate of impairment was found in the verbal function domain (18%) and the highest rate of impairment in the domain of information processing (32%). Fatigue and depression were found in 78% and 55% of all PwBMS, with no difference in these rates between PwBMS and PwNBMS (p = 0.787 and p = 0.316 resp.) CONCLUSION: Cognitive impairment, fatigue and depression are common among people with an EDSS-based definition of benign MS. These aspects should be incorporated into a new and better definition of truly benign MS.

3D printer platform and conductance feedback loop for automated imaging of uneven surfaces by liquid microjunction-surface sampling probe mass spectrometry.

RATIONALE: Molecular imaging of samples using mass spectrometric techniques, such as matrix-assisted laser desorption ionization or desorption electrospray ionization, requires the sample surface to be even/flat and sliced into thin sections (c. 10 µm). Furthermore, sample preparation steps can alter the analyte composition of the sample. The liquid microjunction-surface sampling probe (LMJ-SSP) is a robust sampling interface that enables surface profiling with minimal sample preparation. In conjunction with a conductance feedback system, the LMJ-SSP can be used to automatically sample uneven specimens. METHODS: A sampling stage was built with a modified 3D printer where the LMJ-SSP is attached to the printing head. This setup can scan across flat and even surfaces in a predefined pattern ("static sampling mode"). Uneven samples are automatically probed in "conductance sampling mode" where an electric potential is applied and measured at the probe. When the probe contacts the electrically grounded sample, the potential at the probe drops, which is used as a feedback signal to determine the optimal position of the probe for sampling each location. RESULTS: The applicability of the probe/sensing system was demonstrated by first examining the strawberry tissue using the "static sampling mode." Second, porcine tissue samples were profiled using the "conductance sampling mode." With minimal sample preparation, an area of 11 × 15 mm was profiled in less than 2 h. From the obtained results, adipose areas could be distinguished from non-adipose parts. The versatility of the approach was further demonstrated by directly sampling the bacteria colonies on agar and resected human kidney (intratumoral hemorrhage) specimens with thicknesses ranging from 1 to 4 mm. CONCLUSION: The LMJ-SSP in conjunction with a conductive feedback system is a powerful tool that allows for fast, reproducible, and automated assessment of uneven surfaces with minimal sample preparation. This setup could be used for perioperative assessment of tissue samples, food screening, and natural product discovery, among others.

Cognitive skill learning in multiple sclerosis: A meaningful component of the neuropsychological profile.

Cognitive skill learning (CSL) refers to the capacity to improve performance on specific cognitive operations through repeated practice. We hypothesized that high CSL aptitude may promote accumulation of cognitive reserve, and resiliency to cognitive decline, in people with Multiple Sclerosis (MS). Using an adaptive working memory training paradigm, we obtained CSL aptitude indices (amount of improvement on the training task over time) in MS patients for a single session of practice (25-30 min), and longer-term practice (twenty sessions). Neuropsychological performance was assessed with the Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), and the Raven's Advanced Progressive Matrices (RAPM). CSL aptitude measures were positively correlated with neuropsychological performance, and had high diagnostic accuracy for classifying cognitive impairment in MS, defined as 1.5 SD below the demographics-corrected normative mean of the SDMT. Positive relationships between CSL aptitude measures and neuropsychological performance tended to be more pronounced for individuals with high estimated cognitive reserve, suggesting that high CSL aptitude is a a factor that promotes the protective effects of cognitive reserve. Furthermore, regression analyses indicated that CSL aptitude is separable from baseline cognitive capacity. The findings suggest that CSL aptitude impacts the neuropsychological profile in MS, and may be a factor underlying variance in cognitive resiliency.

Single trial variability in neural activity during a working memory task reveals multiple distinct information processing sequences.

Successful encoding, maintenance, and retrieval of information stored in working memory requires persistent coordination of activity among multiple brain regions. It is generally assumed that the pattern of such coordinated activity remains consistent for a given task. Thus, to separate this task-relevant signal from noise, multiple trials of the same task are completed, and the neural response is averaged across trials to generate an event-related potential (ERP). However, from trial to trial, the neuronal activity recorded with electroencephalogram (EEG) is actually spatially and temporally diverse, conflicting with the assumption of a single pattern of activity for a given task. Here, we show that variability in neuronal activity among single time-locked trials arises from the presence of multiple forms of stimulus dependent synchronized activity (i.e., distinct ERPs). We develop a data-driven classification method based on community detection to identify three discrete spatio-temporal clusters, or subtypes, of trials with different patterns of activation that are further associated with differences in decision-making processes. These results demonstrate that differences in the patterns of neural activity during working memory tasks represent fluctuations in the engagement of distinct brain networks and cognitive processes, suggesting that the brain can choose from multiple mechanisms to perform a given task.

Hyperspectral Visualization-Based Mass Spectrometry Imaging by LMJ-SSP: A Novel Strategy for Rapid Natural Product Profiling in Bacteria.

Mass spectrometry imaging (MSI) has been widely used to discover natural products (NPs) from underexplored microbiological sources. However, the technique is limited by incompatibility with complicated/uneven surface topography and labor-intensive sample preparation, as well as lengthy compound profiling procedures. Here, liquid micro-junction surface sampling probe (LMJ-SSP)-based MSI is used for rapid profiling of natural products from Gram-negative marine bacteria Pseudoalteromonas on nutrient agar media without any sample preparation. A conductance-based autosampling platform with 1 mm spatial resolution and an innovative multivariant analysis-driven method was used to create one hyperspectral image for the sampling area. NP discovery requires general spatial correlation between m/z and colony location but not highly precise spatial resolution. The hyperspectral image was used to annotate different m/z by straightforward color differences without the need to directly interrogate the spectra. To demonstrate the utility of our approach, the rapid analysis of Pseudoalteromonas rubra DSM6842, Pseudoalteromonas tunicata DSM14096, Pseudoalteromonas piscicida JCM20779, and Pseudoalteromonas elyakovii ATCC700519 cultures was directly performed on Agar. Various natural products, including prodiginine and tambjamine analogues, were quickly identified from the hyperspectral image, and the dynamic extracellular environment was shown with compound heatmaps. Hyperspectral visualization-based MSI is an efficient and sensitive strategy for direct and rapid natural product profiling from different Pseudoalteromonas strains.

The moderating roles of self-efficacy and depression in dual-task walking in multiple sclerosis: A test of self-awareness theory.

OBJECTIVE: Multiple sclerosis (MS) is a debilitating neurological disease associated with a variety of psychological, cognitive, and motoric symptoms. Walking is among the most important functions compromised by MS. Dual-task walking (DTW), an everyday activity in which people walk and engage in a concurrent, discrete task, has been assessed in MS, but little is known about how it relates to other MS symptoms. Self-awareness theory suggests that DTW may be a function of the interactions among psychological, cognitive, and motor processes. METHOD: Cognitive testing, self-report assessments for depression and falls self-efficacy (FSE), and walk evaluations [DTW and single-task walk (STW)] were assessed in seventy-three people with MS in a clinical care setting. Specifically, we assessed whether psychological factors (depression and FSE) that alter subjective evaluations regarding one's abilities would moderate the relationships between physical and cognitive abilities and DTW performance. RESULTS: DTW speed is related to diverse physical and cognitive predictors. In support of self-awareness theory, FSE moderated the relationship between STW and DTW speeds such that lower FSE attenuated the strength of the relationship between them. DTW costs - the change in speed normalized by STW speed - did not relate to cognitive and motor predictors. DTW costs did relate to depressive symptoms, and depressive symptoms moderated the effect of information processing on DTW costs. CONCLUSIONS: Findings indicate that an interplay of physical ability and psychological factors - like depression and FSE - may enhance understanding of walking performance under complex, real-world, DTW contexts.

Ultrahigh-Throughput Intact Protein Analysis with Acoustic Ejection Mass Spectrometry.

The need for high-throughput intact protein analysis has been rising as drug discovery increasingly requires the analysis of large sets of covalent modifiers and protein therapeutics. Liquid chromatography-mass spectrometry (LC-MS) is the primary analytical tool used to date to characterize proteins within the biopharmaceutical industry. However, the speed of LC-MS prevents the analysis of large-scale sample sets (>1000 within a day). Acoustic ejection mass spectrometry (AEMS) has recently been established as an electrospray ionization (ESI)-MS based platform with both fast analytical throughput and high data quality. Since its introduction, this technology has been applied in numerous fields with a primary focus on small-molecule analysis in high-throughput drug discovery and development. Here we explore the application of AEMS to high-throughput intact protein analysis for proteins ranging in molecular weight from 17 to 150 kDa on a prototype high-resolution quadrupole time-of-flight (HR QTOF) based AEMS system. Data quality obtained on this platform is comparable to LC-MS, while the analysis speed is significantly improved to one-second-per-sample. This ultrahigh-throughput intact protein analysis platform has the potential to be used broadly in drug discovery.

Cognitive impairment in people with multiple sclerosis: Perception vs. performance - factors that drive perception of impairment differ for patients and clinicians.

BACKGROUND: Neurologists' perceptions of the presence of cognitive impairment (CI) in people with multiple sclerosis (PwMS) may not always align with findings of objective cognitive assessment. The accuracy of self-reported CI in PwMS can also be highly variable across individuals, and may not align with objective measurement of cognitive disturbances. Research suggests that additional factors impact perceived cognitive ability, such as depression and fatigue. Objective cognitive screening regardless of patient or neurologist perception has been recommended but still is often limited in routine care. Moreover, comprehensive neuropsychological assessment is even less routinely done. OBJECTIVE: To explore how neurologists' perceptions of PwMS' CI compare to the perception of the patient by determining whether PwMS and their clinicians are accurate in detecting the presence and degree of CI as defined by a multi-domain validated computerized test battery in PwMS, as well as investigate what factors influence perception of CI in each group. METHODS: PwMS completed a computerized multi-domain cognitive testing battery, and self-reported measures of disease impact (MSIS-29), fatigue (MFIS), and depression (BDI-II). Disability was assessed by the clinician using the Expanded Disability Status Scale (EDSS). Clinicians and patients also provided an estimation of cognitive deficits along a Likert scale. RESULTS: In this cohort of PwMS (N=202, age range: 20 to 88, gender: 71% female), their level of accuracy in detecting attention deficits (k = -.028, p = .010) was low but statistically significant. In contrast, clinicians' accuracy in detecting global CI (k = -.037, p < .001) and a number of specific domain deficits was moderate. Fatigue (p < .001) and cognitive performance (p = .012) significantly predicted patient perceived cognitive deficits. Clinician perceived cognitive performance was significantly predicted by multiple factors: cognitive scores (p < .001), physical disability (p = .011), age (p = .021), and depression (p = .038). CONCLUSION: The need to objectively screen for CI in PwMS, regardless of perception, can be aided by a better understanding of the agreement and discrepancies between the patient and clinician regarding perceived cognitive disturbances and the presence of CI defined by a multi-dimensional objective screening battery.

Examination of the temporal-spatial dynamics of working memory training-induced neuroplasticity.

Efficient working memory (WM) performance involves the dynamic coordination of neural activity on a millisecond time-scale. However, the correspondence between the timing and spatial localization of changes in neural activity following targeted WM training has not been well-established. To address this, we used an event-related potential (ERP) source localization approach to identify the patterns of cortical activity changes that are induced by WM training along both the temporal and spatial dimensions. Healthy adult participants completed approximately 20 sessions of training on either a WM training protocol (visual-letter n-back task), or a control training protocol (visual-letter search task). ERP measures were obtained before and after training (pretest and posttest) for a letter 3-back task. A beamformer source localization method was applied to the ERP data in the N2 (approximately 200-350 msec post-stimulus) and P3 (approximately 300-600 msec post-stimulus) component time windows to identify the cortical activity associated with WM training at distinct stages of information processing. Pretest-to-posttest cortical activity changes that corresponded with WM training gains were observed within the N2 time window, but not the P3 time window. Within the WM training group, training-related enhancement of N2 source activity in bilateral medial orbitofrontal cortex, left rostral anterior cingulate, and right posterior cingulate cortex was significantly associated with behavioral performance improvements on the trained task and untrained tasks of WM. The findings suggest that medial orbitofrontal and cingulate enhancement within 200-350 msec after stimulus onset represents a target for WM training and an important inflection point along the spatial-temporal dimensions of cortical activity for the enhancement of WM performance.

Individual differences in visual evoked potential latency are associated with variance in brain tissue volume in people with multiple sclerosis: An analysis of brain function-structure correlates.

Visual evoked potentials (VEP) index visual pathway functioning, and are often used for clinical assessment and as outcome measures in people with multiple sclerosis (PwMS). VEPs may also reflect broader neural disturbances that extend beyond the visual system, but this possibility requires further investigation. In the present study, we examined the hypothesis that delayed latency of the P100 component of the VEP would be associated with broader structural changes in the brain in PwMS. We obtained VEP latency for a standard pattern-reversal checkerboard stimulus paradigm, in addition to Magnetic Resonance Imaging (MRI) measures of whole brain volume (WBV), gray matter volume (GMV), white matter volume (WMV), and T2-weighted fluid attenuated inversion recovery (FLAIR) white matter lesion volume (FLV). Correlation analyses indicated that prolonged VEP latency was significantly associated with lower WBV, GMV, and WMV, and greater FLV. VEP latency remained significantly associated with WBV, GMV, and WMV even after controlling for the variance associated with inter-ocular latency, age, time between VEP and MRI assessments, and other MRI variables. VEP latency delays were most pronounced in PwMS that exhibited low volume in both white and gray matter simultaneously. Furthermore, PwMS that had delayed VEP latency based on a clinically relevant cutoff (VEP latency ≥ 113 ms) in both eyes had lower WBV, GMV, and WMV and greater FLV in comparison to PwMS that had normal VEP latency in one or both eyes. The findings suggest that PwMS that have delayed latency in both eyes may be particularly at risk for exhibiting greater brain atrophy and lesion volume. These analyses also indicate that VEP latency may index combined gray matter and white matter disturbances, and therefore broader network connectivity and efficiency. VEP latency may therefore provide a surrogate marker of broader structural disturbances in the brain in MS.

Prolonged visual evoked potential latency predicts longitudinal worsening of fatigue in people with multiple sclerosis.

BACKGROUND: Fatigue is a common problem experienced by people with multiple sclerosis (PwMS) and can impact physical, cognitive, and psychosocial aspects of daily living and quality of life. The tracking of meaningful longitudinal change in subjective fatigue that occurs as a result of MS activity may be enhanced by incorporating objective neurophysiological measures into longitudinal assessment. To examine this possibility, we examined the longitudinal relationship between visual evoked potential (VEP) measures and a variety of fatigue measures over an approximately two-year period in PwMS. METHODS: VEP measures were obtained using a checkerboard pattern-reversal paradigm. Fatigue was assessed with the Modified Fatigue Impact Scale (MFIS Global, Physical, Cognitive, and Psychosocial subscales) and the Fatigue Severity Scale (FSS) questionnaires. Multiple linear regression analyses were conducted in which the change in each fatigue scale score from baseline to follow-up (T1-to-T2) served as the outcome variables for separate models. Predictor variables included the peak latency of the P100 component of the VEP (maximum peak among the two eyes) and the inter-ocular latency (IOL) at T1, the T1-to-T2 change score for maximum VEP latency and IOL, and the fatigue score at T1 that corresponded to each outcome measure. RESULTS: Prolonged baseline VEP latency was a significant predictor of the T1-to-T2 increase in MFIS Global score, and increased VEP latency from baseline to follow-up was significantly associated with MFIS Cognitive score over the same time period. Furthermore, VEP latency measures in these two models were better predictors of changes in fatigue than baseline fatigue scores were, based on the magnitude of the standardized beta coefficients. Subsequent post-hoc analyses revealed that the relationship between change in VEP latency and change in MFIS Cognitive score was evident primarily for PwMS that had elevated MFIS Cognitive score at baseline. CONCLUSION: The present study provides novel evidence that prolonged VEP latency is predictive of worsening of global and cognitive fatigue in PwMS. VEP latency measures may therefore provide clinical utility for monitoring changes in fatigue in PwMS, when used in conjunction with other clinical tools.

Discontinuously Dewetting Solvent Arrays: Droplet Formation and Poly-Synchronous Surface Extraction for Mass Spectrometry Imaging Applications.

We describe a new liquid tissue stamping method called poly-synchronous surface extraction (PSSE) that utilizes an omniphobic substrate patterned with hydrophilic surface energy traps (SETs), which when wet with a solvent form a dense microdroplet array. When contacted with a tissue sample, each droplet locally extracts analytes from the tissue surface, which subsequentially can be analyzed by matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-IMS) or ambient ionization-MS techniques. Optimization of the patterned surface with six different solvents was carried out to increase the droplet density, height, and reproducibility of volume deposition. Once optimized, sister slices of a strawberry (Fragaria × ananassa) were spatially extracted using the PSSE technique and the chemical distribution of selected compounds was analyzed with both MALDI-IMS and a lower resolution but faster ambient liquid microjunction surface sampling probe (LMJ-SSP) approach. Heat maps for target analytes for the PSSE approach are compared to those produced using traditional MALDI-IMS analysis. The PSSE method aligned well with direct analysis and demonstrated the potential to increase the speed of ambient MS tissue imaging techniques by decreasing the number of steps required for sample preparation.