Juan Li

Dr. Juan Li

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Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 September 2019 in Science Translational Medicine
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Journal Article
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BSBojan Shutinoski
Bojan Shutinoski
MHMansoureh Hakimi
Mansoureh Hakimi
IHIrene E. Harmsen
Irene E. Harmsen
MLMichaela Lunn
Michaela Lunn
JRJuliana Rocha
Juliana Rocha
MSMichael Schlossmacher
Michael Schlossmacher
The Lrrk2 gene modulates the course of infections in mice in a sex-dependent manner.

10 November 2019 in Journal of Educational and Behavioral Statistics
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Journal Article
Closed access
JRJames Ramsay
James Ramsay
MWMarie Wiberg
Marie Wiberg
JLJuan Li
Juan Li
Ramsay and Wiberg used a new version of item response theory that represents test performance over nonnegative closed intervals such as [0, 100] or [0, n] and demonstrated that optimal scoring of binary test data yielded substantial improvements in point-wise root-mean-squared error and bias over number right or sum scoring. We extend these results by showing that optimal scoring of the full information in option choices produces about as much further improvement in these measures of score performance as was achieved by going from sum scoring to optimal binary scoring.

15 December 2020 in Psych
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Journal Article
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James RamsayJames Ramsay
James Ramsay
JLJuan Li
Juan Li
Marie WibergMarie Wiberg
Marie Wiberg
Diagnostic scales are essential to the health and social sciences, and to the individuals that provide the data. Although statistical models for scale data have been researched for decades, it remains nearly universal that scale scores are sums of weights assigned a priori to question choice options (sum scores), respectively. We propose several modifications of psychometric testing theory that together demonstrate remarkable improvements in the quality of rating scale scores. Our model represents performance as a space with a metric structure by transforming probability into surprisal or information. The estimation algorithm permits the analysis of data from tens and hundreds of thousands of test takers in a few minutes on consumer level computing equipment. Standard errors of performance estimates are shown to be as small as a quarter of those of sum scores. Open access software resources are presented.

23 April 2025 in npj Parkinson's Disease
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Journal Article
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JLJuan Li
Juan Li
KGKelsey Grimes
Kelsey Grimes
JSJoseph Saade
Joseph Saade
JTJulianna J. Tomlinson
Julianna J. Tomlinson
Tiago A. MestreTiago A. Mestre
Tiago A. Mestre
MSMichael Schlossmacher
Michael Schlossmacher
To develop a simplified smell test for identifying patients with Parkinson’s disease (PD), we reevaluated the Sniffin’-Sticks-Identification-Test (SST-ID) and University-of-Pennsylvania-Smell-Identification-Test (UPSIT), using three case-control studies. These included 301 patients with PD or dementia with Lewy bodies (DLB), 68 subjects with multiple-system atrophy (MSA) or progressive supranuclear palsy (PSP), and 281 healthy controls (HC). Scents were ranked by area-under-the-curve values for group classification and results leveraged by 8 published studies with 5853 individuals. PD/DLB patients showed markedly worse olfaction than controls, whereas scores for MSA/PSP subjects were intermediate. We identified and validated a subset of 7 shared odorants that performed similarly to the traditional 16-scent SST-ID and 40-scent UPSIT tests in distinguishing PD/DLB from HC. There, the identification of 4 or fewer scents out of 7 served as an effective cut-off between the two groups. We also identified a critical role for distractors (from correct answers) and age on olfaction performance.

27 April 2020 in bioRxiv
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DKDaniel N. El Kodsi
Daniel N. El Kodsi
JTJacqueline M. Tokarew
Jacqueline M. Tokarew
RSRajib Sengupta
Rajib Sengupta
NLNathalie A. Lengacher
Nathalie A. Lengacher
ANAndy C. Ng
Andy C. Ng
MSMichael Schlossmacher
Michael Schlossmacher
SUMMARY: We recently hypothesized that parkin plays a role in redox homeostasis and provided evidence that it directly reduces hydrogen peroxide (H 2 O 2 ) in vitro . Here, we examined this anti-oxidant activity in vivo . Informed by findings in human brain, we demonstrate that elevated oxidative stress promotes parkin insolubility in mice. In normal mouse brain parkin was partially oxidized, e.g ., at cysteines 195 and 252, which was augmented by oxidative stress. Although under basal conditions H 2 O 2 levels were unchanged in adult prkn -/- brain, a parkin-dependent reduction of cytosolic H 2 O 2 was observed when mitochondria were impaired, either due to neurotoxicant exposure (MPTP) or Sod2 haploinsufficiency. In accordance, markers of oxidative stress, e.g ., protein carbonylation and nitrotyrosination, were elevated in the cytosol but not in mitochondria from prkn -/- mice. Nevertheless, this rise in oxidative stress led to changes in mitochondrial enzyme activities and the metabolism of glutathione in cells and mammalian brain. In parkin’s absence reduced glutathione concentrations were increased including in human cortex. This compensation was not due to new glutathione synthesis but attributed to elevated oxidized glutathione (GSSG)-reductase activity. Moreover, we discovered that parkin also recycled GSSG to its reduced form. With this reaction, parkin became S-glutathionylated, e.g ., at cysteines 59 and human-specific 95. This oxidative modification was reversed by glutaredoxin. Our results demonstrate that cytosolic parkin mediates anti-oxidant reactions including H 2 O 2 reduction and glutathione regeneration. These reducing activities lead to a range of oxidative modifications in parkin itself. In parkin-deficient brain oxidative stress rises despite changes to maintain redox balance.

6 November 2023 in Journal of Educational and Behavioral Statistics
Verified
Journal Article
Open access
JWJoakim Wallmark
Joakim Wallmark
JRJames O. Ramsay
James O. Ramsay
JLJuan Li
Juan Li
Marie WibergMarie Wiberg
Marie Wiberg
Item response theory (IRT) models the relationship between the possible scores on a test item against a test taker’s attainment of the latent trait that the item is intended to measure. In this study, we compare two models for tests with polytomously scored items: the optimal scoring (OS) model, a nonparametric IRT model based on the principles of information theory, and the generalized partial credit (GPC) model, a widely used parametric alternative. We evaluate these models using both simulated and real test data. In the real data examples, the OS model demonstrates superior model fit compared to the GPC model across all analyzed datasets. In our simulation study, the OS model outperforms the GPC model in terms of bias, but at the cost of larger standard errors for the probabilities along the estimated item response functions. Furthermore, we illustrate how surprisal arc length, an IRT scale invariant measure of ability with metric properties, can be used to put scores from vastly different types of IRT models on a common scale. We also demonstrate how arc length can be a viable alternative to sum scores for scoring test takers.