About

Xin Tu is a professor at the Herbert Wertheim School of Public Health & Human Longevity Science at UCSD. His research focuses on various aspects of public health, including longitudinal T-cell phenotypic dynamics during sustained antiretroviral therapy in people with HIV, associations between environmental exposures such as insecticide metabolites and neurocognitive performance, and the role of inflammation biomarkers in neurobehavioral performance among adolescents. His work also explores the relationships between loneliness, cognitive function, and mental health in populations with schizophrenia and other psychiatric conditions. Additionally, Tu investigates the impact of environmental health factors, including PFAS and pesticides, on lung function and metabolic health from adolescence to young adulthood. His contributions extend to understanding the biological mechanisms underlying cardiovascular and neurological diseases, as well as the social and behavioral determinants of health, with a particular emphasis on vulnerable populations.

Research topics

• Medicine
• Internal medicine
• Gastroenterology
• Psychology
• Biology
• Gerontology
• Genetics
• Psychiatry
• Bioinformatics
• Radiology
• Virology
• Environmental health
• Clinical psychology
• Economics
• Neuroscience
• Audiology

Selected publications

• Low-Noise Uncooled Quartz-Based Very Long Wave Infrared Detector

  Photonics Research · 2026-04-17

  article
  PublisherDOI

• Within-Person Fluctuations in Momentary Loneliness Among People with Schizophrenia

  International Journal of Social Psychiatry · 2025-10-31

  articleOpen access

  BACKGROUND: Loneliness is highly prevalent among individuals with schizophrenia and contributes to poor functional and clinical outcomes. However, most research to date has relied on trait-based assessments, providing limited insight into the dynamic nature of loneliness experiences. AIMS: The current study employed ecological momentary assessment (EMA) to examine momentary loneliness and its variability in people with schizophrenia relative to a comparison group of participants without a history of serious mental illness (NC). METHODS: Participants included 104 adults (39 with schizophrenia or schizoaffective disorder and 65 NC). Participants completed up to 28 EMA surveys over seven consecutive days. RESULTS: Participants with schizophrenia reported significantly higher trait and momentary loneliness, as well as greater between-person and within-person variability in momentary loneliness. Trait loneliness was moderately associated with momentary loneliness but did not account for the elevated within-person variability observed in the schizophrenia group. CONCLUSIONS: Findings underscore the importance of considering both chronic and dynamic features of loneliness in schizophrenia and highlight the potential value of real-time assessment for informing targeted interventions.

  PublisherDOI

• Pesticide and Liver Biomarkers Among Ecuadorian Adolescents and Adults Living in Agricultural Settings

  Toxics · 2025-08-18 · 2 citations

  articleOpen access

  Background: Experimental studies suggest that some insecticides, fungicides, and herbicides can result in liver cell death, but population-based evidence is lacking. We investigated associations between urinary pesticide metabolites and liver biomarkers among adolescents and adults in an Ecuadorian agricultural area. Methods: We examined participants in 2016 (N = 528, 11–17 years) and 2022 (N = 505, 17–24 years). Plasma alanine aminotransferase (ALT), aspartate aminotransferase, soluble cytokeratin-18, and erythrocytic acetylcholinesterase were measured. Urinary biomarkers included four organophosphates, six neonicotinoids, three pyrethroids, two herbicides, and two fungicides. Generalized estimating equation (GEE) models examined associations and introduced sex and age interaction terms and quadratic terms. Quantile g-computation evaluated the effects of pesticide mixtures. Results: No significant associations were observed between pesticide biomarkers and liver biomarkers in longitudinal or cross-sectional analyses. A curvilinear association was found between 3-phenoxybenzoic acid (3-PBA; pyrethroid) and ALT (βquadratic = −0.35, 95% CI: [−0.67, −0.04]) in 2016, but not in 2022. Sex modified the associations of 3-PBA with AST, ALT, and CK18-M65 in adolescents (2016), with non-significant positive associations observed in males and non-significant negative associations observed in females. No pesticide mixture effects were observed. Conclusions: Urinary biomarkers of various insecticides, herbicides, fungicides, and their mixtures were not associated with liver biomarkers among adolescents and young adults in agricultural settings. These largely null findings, consistent across time points, suggest background-level exposures in these settings possibly do not harm liver health in this population, though effects at higher exposures cannot be ruled out.

  PublisherOA PDFDOI

• Time Attitude Latent Profiles and Influencing Factors Among Chinese Adolescents

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Semiparametric Regression Models for Explanatory Variables with Missing Data due to Detection Limit

  ArXiv.org · 2025-07-13

  preprintOpen accessSenior author

  Detection limit (DL) has become an increasingly ubiquitous issue in statistical analyses of biomedical studies, such as cytokine, metabolite and protein analysis. In regression analysis, if an explanatory variable is left-censored due to concentrations below the DL, one may limit analyses to observed data. In many studies, additional, or surrogate, variables are available to model, and incorporating such auxiliary modeling information into the regression model can improve statistical power. Although methods have been developed along this line, almost all are limited to parametric models for both the regression and left-censored explanatory variable. While some recent work has considered semiparametric regression for the censored DL-effected explanatory variable, the regression of primary interest is still left parametric, which not only makes it prone to biased estimates, but also suffers from high computational cost and inefficiency due to maximizing an extremely complex likelihood function and bootstrap inference. In this paper, we propose a new approach by considering semiparametric generalized linear models (SPGLM) for the primary regression and parametric or semiparametric models for DL-effected explanatory variable. The semiparametric and semiparametric combination provides the most robust inference, while the semiparametric and parametric case enables more efficient inference. The proposed approach is also much easier to implement and allows for leveraging sample splitting and cross fitting (SSCF) to improve computational efficiency in variance estimation. In particular, our approach improves computational efficiency over bootstrap by 450 times. We use simulated and real study data to illustrate the approach.

  PublisherOA PDFDOI

• Testing the causal impact of plasma amyloid on total Tau using a genetically informative sample of adult male twins

  Aging Brain · 2025-01-01

  articleOpen access

  The amyloid cascade hypothesis predicts that amyloid-beta (Aβ) aggregation drives tau tangle accumulation. We tested competing causal and non-causal hypotheses regarding the direction of causation between Aβ40 and Aβ42 and total Tau (t-Tau) plasma biomarkers. Plasma Aβ40, Aβ42, t-Tau, and neurofilament light chain (NFL) were measured in 1,035 men (mean = 67.0 years) using Simoa immunoassays. Genetically informative twin modeling tested the direction of causation between Aβs and t-Tau. No clear evidence that Aβ40 or Aβ42 directly causes t-Tau was observed. Instead, the alternative causal hypotheses also fit the data well. In contrast, exploratory analyses suggested a causal impact of the Aβ biomarkers on NFL. Separately, reciprocal causation was observed between t-Tau and NFL. Plasma Aβ40 or Aβ42 do not appear to have a direct causal impact on t-Tau, though our use of total rather than phosphorylated tau was a limitation. In contrast, Aβ biomarkers appeared to causally impact NFL in cognitively unimpaired men in their late 60 s.

  PublisherDOI

• Evolutionary game analysis of strategic organizational knowledge synergy in collaborative innovation

  Scientific Reports · 2025-12-05 · 1 citations

  articleOpen access1st authorCorresponding

  Government-industry-university-institute (GIUI) collaborative innovation is widely acknowledged as a core driver of innovation-driven growth. However, many collaborations remain superficial due to fragmented resource allocation and misaligned incentives. This paper adopts an exploratory case study approach to analyze successful cases from South China University of Technology, proposes the strategic-organizational-knowledge synergy framework, applies evolutionary game theory to construct a tripartite evolutionary game model involving government, industry, universities, and institutes, and simulates the impact of strategic, organizational, and knowledge-based elements on collaborative innovation. The findings reveal that the strategic synergy mechanism serves as the foundation for GIUI collaborative innovation, organizational synergy provides structural support, and knowledge synergy acts as the critical enabler. The deep integration and sustainable development of GIUI collaborative innovation rely on the coordinated input of strategic, organizational, and knowledge-based elements, as well as comprehensive system-level contributions.

  PublisherOA PDFDOI

• Non-Linear Relationships of Loneliness with Age in People Living with Schizophrenia and Non-Psychiatric Comparison Participants: Relations non linéaires entre la solitude et l’âge chez les personnes atteintes de schizophrénie et les personnes n’ayant aucun antécédent de maladie psychiatrique

  The Canadian Journal of Psychiatry · 2025-07-28 · 1 citations

  articleOpen access

  Objective: Loneliness – distress that arises from discrepancies between perceived and desired relationships – is increasingly prevalent and recognized as a major public health concern due to the association with negative health outcomes. People living with schizophrenia (PLWS) experience higher rates of loneliness than the general population and may be particularly vulnerable to these adverse outcomes. In the general population, loneliness fluctuates throughout the lifespan, but the relationship between loneliness and age in PLWS is not well understood. Method: 271 adults, 141 adults with a diagnosis of schizophrenia or schizoaffective disorder (PLWS)and 130 adults with no history of major psychiatric illness (NCs) aged 27–69 completed clinical interviews and self-report measures assessing loneliness, perceived social support, and mental and physical health. Participants also completed blood draws for biomarkers of inflammation and hyperglycaemia. Locally Weighted Scatterplot Smoothing (LOWESS) regression modelling was used to examine potential non-linear relationships between loneliness and age for both groups and to select the polynomial that best fit the observed relationship. Results: We observed an age by diagnostic group interaction (log estimate = −0.005, SE = 0.003) such that PLWS reported higher loneliness scores compared to NCs of similar age. Patterns of loneliness differed with age between diagnostic groups such that loneliness remained relatively stable and high for PLWS while for NCs loneliness increased from age 40 to age 60. In both groups, loneliness was associated with worse self-reported physical health, depression, and, among PLWS, positive symptoms. Conclusion: Results suggest different patterns of loneliness across adulthood for PLWS and NC, reflecting the different social milestones for NCs during this age period that are not as commonly experienced by PLWS, such as marriage, empty nesting and retirement. Loneliness is linked with poor physical and mental health outcomes among PLWS and may be an important target for improving morbidity and mortality for PLWS.

  PublisherOA PDFDOI

• Esculetin inhibits liver cancer by targeting glucose-6-phosphate isomerase mediated glycolysis

  Biomedicine & Pharmacotherapy · 2025-05-14 · 5 citations

  articleOpen access

  BACKGROUND: Liver cancer is challenging to detect in its early stages, and the global incidence rate and mortality associated with this disease have reached alarming levels. Currently, treatment options for liver cancer are limited, and there is a significant lack of safe and effective therapeutic agents. Esculetin is a natural product, exhibits almost non-toxic and inhibitory properties against various malignancies, making it a subject worthy of further investigation in liver cancer. METHODS: In this study, potential targets of esculetin in liver cancer were identified through transcriptomics, network pharmacology, and molecular docking technologies, and gene interference. Direct binding targets of esculetin were identified using surface plasmon resonance (SPR). The molecular mechanisms by which esculetin affects glucose metabolism in liver cancer were also explored. Finally, the activity against liver cancer and mechanisms of action of esculetin were validated in vivo using a mouse tumor model. RESULTS: Glucose-6-phosphate isomerase (GPI) was shown to have a direct binding affinity for this compound. Esculetin inhibits glycolysis in liver cancer through its interaction with GPI and it was shown to exert a significant inhibitory effect on the genes and proteins associated with glycolysis such as ALDOA, ENO1, GAPDH, LDHA, PFKL, PGAM1, PGK1, and PKM2. Furthermore, esculetin not only suppresses the growth of liver cancer cells in vitro but also exhibits notable anti-tumor effects in vivo. CONCLUSIONS: This study demonstrated the inhibitory effects of esculetin against liver cancer both in vitro and in vivo, demonstrating inhibition of glycolysis in liver cancer cells. In addition, the key glycolysis enzyme GPI was identified as a direct target of esculetin.

  PublisherDOI

• Semiparametric rank-based regression models as robust alternatives to parametric mean-based counterparts for censored responses under detection-limit

  ArXiv.org · 2025-12-11

  preprintOpen accessSenior author

  Detection limits are common in biomedical and environmental studies, where key covariates or outcomes are censored below an assay-specific threshold. Standard approaches such as complete-case analysis, single-value substitution, and parametric Tobit-type models are either inefficient or sensitive to distributional misspecification. We study semiparametric rank-based regression models as robust alternatives to parametric mean-based counterparts for censored responses under detection limits. Our focus is on accelerated failure time (AFT) type formulations, where rank-based estimating equations yield consistent slope estimates without specifying the error distribution. We develop a unifying simulation framework that generates left- and right-censored data under several data-generating mechanisms, including normal, Weibull, and log-normal error structures, with detection limits or administrative censoring calibrated to target censoring rates between 10\% and 60\%. Across scenarios, we compare semiparametric AFT estimators with parametric Weibull AFT, Tobit, and Cox proportional hazards models in terms of bias, empirical variability, and relative efficiency. Numerical results show that parametric models perform well only under correct specification, whereas rank-based semiparametric AFT estimators maintain near-unbiased covariate effects and stable precision even under heavy censoring and distributional misspecification. These findings support semiparametric rank-based regression as a practical default for censored regression with detection limits when the error distribution is uncertain. Keywords: Semiparametric models, Estimating equations, Left censoring, Right censoring, Tobit regression, Efficiency

  PublisherOA PDFDOI

Recent grants

• NIH Grant R29AI036627

  NIH · $453k · 2000

Frequent coauthors

• Bonnie Bruce

  Emory University

  140 shared

• Ellen Lee

  Institute on Aging

  131 shared

• Hua He

  Tibet Autonomous Region People's Hospital

  129 shared

• Julie Falardeau

  129 shared

• Anil D. Patel

  Rajiv Gandhi Cancer Institute and Research Centre

  129 shared

• Byron L. Lam

  Miami Dermatology and Laser Institute

  129 shared

• Robert Granadier

  Beaumont Health

  129 shared

• Reid Longmuir

  Vanderbilt University Medical Center

  129 shared

Education

• Ph.D., Public Health

  University of California, San Diego

  2005

• M.S., Environmental Health Sciences

  University of California, San Diego

  2001

• B.S., Environmental Health Sciences

  University of California, San Diego

  1999