Addition of constitutional symptoms to the SLEDAI-2K improves overall disease activity assessment: A pilot study.

OBJECTIVE: Constitutional symptoms (fatigue, lymphadenopathy, and weight loss) are not included in the SLE disease activity index-2000 (SLEDAI-2K). In this pilot study, we assessed the concurrent and construct validity of a revised SLEDAI-2K (SLED-R) that included these symptoms with the original SLEDAI-2K (SLED-O), using the physician global assessment of disease activity (PGA) as the reference. METHODS: Our revised SLED-R substituted the SLED-O's fever descriptor with a constitutional descriptor that included fever, fatigue, lymphadenopathy, and/or weight loss. SLED-O, SLED-R, PGA and patient global assessment (PtGA) scores were collected prospectively. Bland-Altman correlations for repeated measures were calculated and Meng's z-test was used to compare correlations between dependent and overlapping correlation coefficients. Associations between constitutional symptoms and disease activity measures were analyzed using Mann-Whitney U, Kruskal-Wallis, Chi-square tests and repeated measures correlations. RESULTS: 1123 SLED-O, SLED-R, PGA, and 1066 PtGA were collected in 239 subjects. The new descriptor was scored in 45 subjects (18.8%) and 92 instances (8.1%), while the original descriptor, fever, was scored in only 4 subjects (1.7%) and 5 instances (0.4%). Mean SLED-O, PGA and PtGA scores were higher when the constitutional descriptor was scored versus not (p < .001). The correlation between SLED-R and PGA was marginally higher than between SLED-O and PGA (p < .001). Fatigue contributed most to this increase (p = .001) and associated with both higher PGA and PtGA scores (p < .001). Mean SLED-O and PGA scores were higher when ≥1 constitutional symptom(s) were scored versus not (p < .002). Correlations between PGA and PtGA when the new descriptor was scored versus not were similar (p = .860). The frequency of concordance between PGA and PtGA was lower when the new descriptor was scored (55%) versus not (72.5%), with PGA > PtGA when the new descriptor was scored (p < .001). CONCLUSION: The addition of constitutional symptoms to SLEDAI-2K, particularly fatigue, resulted in a marginal increase in its correlation with PGA, and new constitutional symptoms associated with higher SLED-O and PGA scores. As fatigue is subjective and difficult to attribute to SLE, its validity and inter-rater reliability in scoring remains uncertain. The clinical utility of SLED-R remains unclear, and further studies of its validity and reliability are needed.

Are Metrics Enough? Guidelines for Communicating and Visualizing Predictive Models to Subject Matter Experts.

Presenting a predictive model's performance is a communication bottleneck that threatens collaborations between data scientists and subject matter experts. Accuracy and error metrics alone fail to tell the whole story of a model - its risks, strengths, and limitations - making it difficult for subject matter experts to feel confident in their decision to use a model. As a result, models may fail in unexpected ways or go entirely unused, as subject matter experts disregard poorly presented models in favor of familiar, yet arguably substandard methods. In this paper, we describe an iterative study conducted with both subject matter experts and data scientists to understand the gaps in communication between these two groups. We find that, while the two groups share common goals of understanding the data and predictions of the model, friction can stem from unfamiliar terms, metrics, and visualizations - limiting the transfer of knowledge to SMEs and discouraging clarifying questions being asked during presentations. Based on our findings, we derive a set of communication guidelines that use visualization as a common medium for communicating the strengths and weaknesses of a model. We provide a demonstration of our guidelines in a regression modeling scenario and elicit feedback on their use from subject matter experts. From our demonstration, subject matter experts were more comfortable discussing a model's performance, more aware of the trade-offs for the presented model, and better equipped to assess the model's risks - ultimately informing and contextualizing the model's use beyond text and numbers.

UnProjection: Leveraging Inverse-Projections for Visual Analytics of High-Dimensional Data.

Projection techniques are often used to visualize high-dimensional data, allowing users to better understand the overall structure of multi-dimensional spaces on a 2D screen. Although many such methods exist, comparably little work has been done on generalizable methods of inverse-projection - the process of mapping the projected points, or more generally, the projection space back to the original high-dimensional space. In this article we present NNInv, a deep learning technique with the ability to approximate the inverse of any projection or mapping. NNInv learns to reconstruct high-dimensional data from any arbitrary point on a 2D projection space, giving users the ability to interact with the learned high-dimensional representation in a visual analytics system. We provide an analysis of the parameter space of NNInv, and offer guidance in selecting these parameters. We extend validation of the effectiveness of NNInv through a series of quantitative and qualitative analyses. We then demonstrate the method's utility by applying it to three visualization tasks: interactive instance interpolation, classifier agreement, and gradient visualization.

Associations between circulating interferon and kynurenine/tryptophan pathway metabolites: support for a novel potential mechanism for cognitive dysfunction in SLE.

OBJECTIVE: Quinolinic acid (QA), a kynurenine (KYN)/tryptophan (TRP) pathway metabolite, is an N-methyl-D-aspartate receptor agonist that can produce excitotoxic neuron damage. Type I and II interferons (IFNs) stimulate the KYN/TRP pathway, producing elevated QA/kynurenic acid (KA), a potential neurotoxic imbalance that may contribute to SLE-mediated cognitive dysfunction. We determined whether peripheral blood interferon-stimulated gene (ISG) expression associates with elevated serum KYN:TRP and QA:KA ratios in SLE. METHODS: ISG expression (whole-blood RNA sequencing) and serum metabolite ratios (high-performance liquid chromatography) were measured in 72 subjects with SLE and 73 healthy controls (HCs). ISG were identified from published gene sets and individual IFN scores were derived to analyse associations with metabolite ratios, clinical parameters and neuropsychological assessments. SLE analyses were grouped by level of ISG expression ('IFN high', 'IFN low' and 'IFN similar to HC') and level of monocyte-associated gene expression (using CIBERSORTx). RESULTS: Serum KYN:TRP and QA:KA ratios were higher in SLE than in HC (p<0.01). 933 genes were differentially expressed ≥2-fold in SLE versus HC (p<0.05). 70 of the top 100 most highly variant genes were ISG. Approximately half of overexpressed genes that correlated with KYN:TRP and QA:KA ratios (p<0.05) were ISG. In 36 IFN-high subjects with SLE, IFN scores correlated with KYN:TRP ratios (p<0.01), but not with QA:KA ratios. Of these 36 subjects, 23 had high monocyte-associated gene expression, and in this subgroup, the IFN scores correlated with both KY:NTRP and QA:KA ratios (p<0.05). CONCLUSIONS: High ISG expression correlated with elevated KYN:TRP ratios in subjects with SLE, suggesting IFN-mediated KYN/TRP pathway activation, and with QA:KA ratios in a subset with high monocyte-associated gene expression, suggesting that KYN/TRP pathway activation may be particularly important in monocytes. These results need validation, which may aid in determining which patient subset may benefit from therapeutics directed at the IFN or KYN/TRP pathways to ameliorate a potentially neurotoxic QA/KA imbalance.

Quinolinic acid, a kynurenine/tryptophan pathway metabolite, associates with impaired cognitive test performance in systemic lupus erythematosus.

OBJECTIVES: Interferon-alpha, an important contributor to SLE pathogenesis, induces the enzyme indoleamine 2,3-dioxygenase in the kynurenine/tryptophan (KYN/TRP) pathway. This leads to a potentially neurotoxic imbalance in the KYN/TRP pathway metabolites, quinolinic acid (QA), an N-methyl D-aspartate glutamatergic receptor (NMDAR) agonist, and kynurenic acid (KA), an NMDAR antagonist. We determined whether QA/KA ratios associate with cognitive dysfunction (CD) and depression in SLE. METHODS: This cross-sectional study included 74 subjects with SLE and 74 healthy control (HC) subjects; all without history of neuropsychiatric disorders. Serum metabolite levels (KYN, TRP, QA, KA) were measured concurrently with assessments of cognition (Automated Neuropsychological Assessment Metrics (ANAM), 2×2 array), mood and pain, and compared between SLE and HC. Multivariable modelling in SLE was used to evaluate associations of metabolites with cognitive performance and depression. RESULTS: Serum KYN/TRP and QA/KA ratios were elevated in SLE versus HC (p<0.0001). SLE performed worse than HC on four of five ANAM tests (all p≤0.02) and the 2×2 array (p<0.01), and had higher depression scores (p<0.01). In SLE, elevated QA/KA ratios correlated with poor performance on Match to Sample (MTS), a working memory and visuospatial processing task (p<0.05). Subjects with SLE with elevated QA/KA ratios also had slightly higher odds of depression, but this did not reach significance (p=0.09). Multivariable modelling in SLE confirmed an association between QA/KA ratios and poor MTS performance when considering potentially confounding factors (p<0.05). CONCLUSIONS: Elevated serum KYN/TRP and QA/KA ratios confirm KYN/TRP pathway activation in SLE. The novel association between increased QA/KA ratios and poor cognitive performance supports further study of this pathway as a potential biomarker or therapeutic target for SLE-mediated CD.

Diagnostic Dilemma of Paraneoplastic Rheumatic Disorders: Case Series and Narrative Review.

Paraneoplastic rheumatic disorder (RD) is a disorder that may present before, concurrent with, or after the diagnosis of malignancy. Paraneoplastic RDs are a clinical expression of occult cancer that is not directly related to a tumor or metastasis and manifests as rheumatoid symptoms. The RD is determined by the organ system affected by articular, muscular, cutaneous, vascular, or miscellaneous symptoms. Each case is challenging to diagnose because cancer may present with similar symptoms as a common rheumatic disorder. Of note, the majority of cases have minimal responsiveness or no responsiveness to standard rheumatoid treatment. Therefore, it is imperative to recognize and treat the underlying cancer accordingly. Herein, we present four different diagnostic dilemma cases of RD: case #1 - leukocytoclastic vasculitis and C3 glomerulopathy, case #2 - scleroderma, case #3 - Raynaud's syndrome and possible lupus-like syndrome, and case #4 - inflammatory myositis. Institutional IRB approval was obtained for this case series. We will discuss and review the literature on each topic. In addition, we will mention a review of paraneoplastic rheumatoid arthritis. As rheumatic disease is associated with the use of immune checkpoint inhibitors (ICIs) for cancer treatment, we will briefly discuss some of the most common rheumatic presentations in the setting of these drugs. This case review aims to inform clinicians about the atypical presentation of paraneoplastic RD and to highlight the need for interdisciplinary management between rheumatologists, oncologists, and primary care practitioners.

TUBERCULOUS CHOROIDITIS IN PATIENT WITH VOGT-KOYANAGI-HARADA DISEASE.

PURPOSE: To describe a novel case of intraocular tuberculosis (TB) arising in a patient undergoing treatment for Vogt-Koyanagi-Harada disease, and to highlight the use of spectral domain optical coherence tomography for helping confirm the diagnosis and monitor treatment response. METHODS: Case report of a patient with Vogt-Koyanagi-Harada disease on prednisone, with acute clinical changes suspicious for bilateral tuberculous choroiditis. Spectral optical coherence tomography, fundus photography, and B-scan ultrasonography were all used to capture the acute lesions, and to monitor their responses after initiation of anti-TB therapy. RESULTS: New subretinal lesions arose bilaterally, as characterized by spectral domain optical coherence tomography, and appeared to regress after a first round of anti-TB therapy, thereby helping confirm the presumed diagnosis of intraocular TB. A new peripheral choroidal lesion arose shortly after temporary cessation of antimicrobial treatment, and again regressed once four-drug therapy was instituted, with no recurrent lesions thereafter. CONCLUSION: The use of multimodal imaging was instrumental in the management of a rare case of intraocular TB arising in the setting of underlying Vogt-Koyanagi-Harada disease.

Metabolic and microstructural alterations in the SLE brain correlate with cognitive impairment.

To address challenges in the diagnosis of cognitive dysfunction (CD) related to systemic lupus erythematosus-associated (SLE-associated) autoimmune mechanisms rather than confounding factors, we employed an integrated approach, using resting-state functional (FDG-PET) and structural (diffusion tensor imaging [DTI]) neuroimaging techniques and cognitive testing, in adult SLE patients with quiescent disease and no history of neuropsychiatric illness. We identified resting hypermetabolism in the sensorimotor cortex, occipital lobe, and temporal lobe of SLE subjects, in addition to validation of previously published resting hypermetabolism in the hippocampus, orbitofrontal cortex, and putamen/GP/thalamus. Regional hypermetabolism demonstrated abnormal interregional metabolic correlations, associated with impaired cognitive performance, and was stable over 15 months. DTI analyses demonstrated 4 clusters of decreased microstructural integrity in white matter tracts adjacent to hypermetabolic regions and significantly diminished connecting tracts in SLE subjects. Decreased microstructural integrity in the parahippocampal gyrus correlated with impaired spatial memory and increased serum titers of DNRAb, a neurotoxic autoantibody associated with neuropsychiatric lupus. These findings of regional hypermetabolism, associated with decreased microstructural integrity and poor cognitive performance and not associated with disease duration, disease activity, medications, or comorbid disease, suggest that this is a reproducible, stable marker for SLE-associated CD that may be may be used for early disease detection and to discriminate between groups, evaluate response to treatment strategies, or assess disease progression.

Click Chemistry-Based DNA Labeling of Cells for Barcoding Applications.

Cell labeling and tracking methodologies can play an important role in experiments aimed at understanding biological systems. However, many current cell labeling and tracking techniques have limitations that preclude their use in a variety of multiplexed and high-throughput applications that could best represent the heterogeneity and combinatorial complexity present in physiologic contexts. Here, we demonstrate an approach for labeling, tracking, and quantifying cells using double-stranded DNA barcodes. These barcodes are introduced to the outside of the cell membrane, giving the labeled cells a unique identifier. This approach is compatible with flow cytometric and PCR-based identification and relative quantification of the presence of barcode-labeled cells. Further, utilizing this strategy, we demonstrate the capacity for sorting and enrichment of barcoded cells from a bulk population. In addition, we illustrate the design and utility of a range of orthogonal barcode sequences, which can enable the use of multiple independent barcodes to track, sort, and enrich multiple cell types and/or cells receiving distinct treatments from a pooled sample. Overall, this method of labeling cells has the potential to track multiple populations of cells in both high-throughput in vitro and physiologic in vivo settings.

Experimental use of an extracellular matrix graft in pterygium surgery.

A 40-year-old man presented with a primary pterygium of the right eye and underwent pterygium excision using mitomycin C and placement of an extracellular matrix (ECM) adjuvant. As an adjuvant in pterygium surgery, ECM serves as a scaffold while promoting the growth of normal conjunctiva. Perioperatively, the ECM graft was found to be easily manipulated on the surgical field. It attached to the scleral bed with fibrin glue without complication. Postoperatively, there was no inflammation or local tissue reaction to the porcine ECM graft. At the most recent follow-up examination, 6 months postoperatively, there were no signs of recurrence of the pterygium past the limbus. This is the first report describing the use of ECM as an adjuvant to pterygium excision.

An improved artifacts removal method for high dimensional EEG.

BACKGROUND: Multiple noncephalic electrical sources superpose with brain signals in the recorded EEG. Blind source separation (BSS) methods such as independent component analysis (ICA) have been shown to separate noncephalic artifacts as unique components. However, robust and objective identification of artifact components remains a challenge in practice. In addition, with high dimensional data, ICA requires a large number of observations for stable solutions. Moreover, using signals from long recordings to provide the large observation set might violate the stationarity assumption of ICA due to signal changes over time. NEW METHOD: Instead of decomposing all channels simultaneously, subsets of channels are randomly selected and decomposed with ICA. With reduced dimensionality of the subsets, much less amount of data is required to derive stable components. To characterize each independent component, an artifact relevance index (ARI) is calculated by template matching each component with a model of the artifact. Automatic artifact identification is then implemented based on the statistical distribution of ARI of the numerous components generated. RESULTS: The proposed permutation resampling for identification matching (PRIM) method effectively removed eye blink artifacts from both simulated and real EEG. COMPARISON WITH EXISTING METHOD: The average topomap correlation coefficient between the cleaned EEG and the ground truth is 0.89±0.01 for PRIM, compared with 0.64±0.05 for conventional ICA based method. The average relative root-mean-square error is 0.40±0.01 for PRIM, compared with 0.66±0.10 for conventional method. CONCLUSIONS: The proposed method overcame limitations of conventional ICA based method and succeeded in removing eye blink artifacts automatically.

Visualization of uncertainty without a mean.

As dataset size and complexity steadily increase, uncertainty is becoming an important data aspect. So, today's visualizations need to incorporate indications of uncertainty. However, characterizing uncertainty for visualization isn't always straightforward. Entropy, in the information-theoretic sense, can be a measure for uncertainty in categorical datasets. The authors discuss the mathematical formulation, interpretation, and use of entropy in visualizations. This research aims to demonstrate entropy as a metric and expand the vocabulary of uncertainty measures for visualization.

Interactive vector field feature identification.

We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.