About

Haiquan Li is an Assistant Professor in the Department of Biosystems Engineering at the University of Arizona. He serves as the Director of Translational Bioinformatics and is also an Assistant Professor in the Department of Statistics-GIDP. His research focuses on biosystems engineering and bioinformatics, contributing to the development of innovative approaches in these fields. He is based in the Shantz Building, Room 403, Tucson, AZ, and can be contacted via email at haiquan@arizona.edu or by phone at 520-621-1890. His work involves integrating biosystems informatics with engineering principles to advance research and education in biosystems analytics and technology.

Research topics

• Biology
• Artificial Intelligence
• Computer Science
• Data Mining
• Botany
• Machine Learning
• Genetics
• Bioinformatics
• Data science
• Evolutionary biology
• Database

Selected publications

• Distribution of Human Papillomavirus (HPV) Infection in Women of Appropriate Age in Beiliu City and Recommendations for Public Health Intervention

  Natural Science · 2025-01-01

  articleOpen access1st authorCorresponding

  Objective: This study aims to analyze the distribution of positive human papillomavirus (HPV) infections among women of appropriate age in Beiliu City during cervical cancer screening in 2024, providing data support for subsequent public health interventions. Methods: A retrospective analysis was conducted on the HPV test results from January 1, 2024, to November 30, 2024, at Beiliu Maternal and Child Health Hospital. We statistically analyzed the positive rates of different HPV genotypes and the co-infection status of multiple genotypes. Results: A total of 7558 individuals were tested, with 1103 positive cases identified, resulting in a positivity rate of 14.59%. Among these, HPV type 52 had the highest positive rate, accounting for 18.47%. The co-infection analysis showed that there were 788 cases with single genotype positivity, 236 with double genotype positivity, and 58 with triple genotype positivity, while cases with multiple genotypes simultaneously positive were relatively rare. Conclusion: The HPV infection rate among women of appropriate age in Beiliu City is relatively high, especially for high-risk HPV types. To reduce the future incidence of cervical cancer, it is recommended to enhance health education and vaccination efforts for this population.

  PublisherOA PDFDOI

• A comprehensive splicing characterization of COL4A5 mutations and prognostic significance in a single cohort with X-linked alport syndrome

  Frontiers in Genetics · 2025-06-11

  articleOpen access1st author

  Introduction: X-linked Alport syndrome (XLAS), caused by mutations in the COL4A5 gene, is an X-linked hereditary disease typically characterized by renal failure, hearing loss, and ocular abnormalities. It is a leading hereditary cause of end-stage renal disease (ESRD) worldwide. Studies on the genotype-phenotype correlation in Alport syndrome suggest that splicing mutations result in more severe clinical phenotypes than missense mutations. Determining whether COL4A5 mutations lead to aberrant mRNA splicing is critical for diagnosis and prognosis. Methods: This study retrospectively reviewed pediatric XLAS patients with COL4A5 gene mutations from a single-center cohort, summarizing and analyzing their clinical features. Minigene assay was employed to evaluate the mRNA splicing functionality of 26 single-nucleotide variants (SNVs), both intronic and exonic, identified in XLAS patients. Bioinformatics tools were used to evaluate the accuracy and sensitivity of splicing mutation prediction. Additionally, linear mixed models were applied to analyze the relationship between mutation types and prognosis in patients' estimated glomerular filtration rate (eGFR), exploring genotype-phenotype correlations. Results: In this cohort, we screened 41 XLAS pediatric patients, including 32 with confirmed XLAS and nine suspected XLAS. The cohort included 21 males (51.2%) and 20 females (48.8%), with a median age at onset of 4.42 years. Among the patients, 22 presented with both hematuria and proteinuria, while 18 exhibited hematuria alone. Notably, only one patient had isolated proteinuria. Regarding mRNA splicing, among the 26 intronic and exonic SNVs, 10 mutations (38.5%) were found to cause aberrant mRNA splicing, as demonstrated by the minigene assay. Sensitivity and specificity assessments of bioinformatics tools revealed that ESE Finder demonstrated higher sensitivity, while RNA Splicer exhibited greater specificity. Furthermore, These splicing abnormalities were closely associated with a faster decline in eGFR. Conclusion: This study demonstrates that 38.5% of SNVs in the COL4A5 gene result in aberrant mRNA splicing, which is closely linked to renal function decline in XLAS. Splicing mutations are correlated with more rapid renal progression, highlighting the importance of determining the splicing effects of SNVs during genetic screening for XLAS.

  PublisherOA PDFDOI

• Immobilisation of endogenous phosphorus and lead in sediments by composite water purification sludge hydrochar

  Environmental Technology · 2025-03-27 · 1 citations

  article

  -LaHyd promoted the endogenous P transformation into stable forms while reducing the bioavailable P fractions. Concurrently, it enhanced Pb passivation, thereby mitigating Pb leaching risks from the sediment.

  PublisherDOI

• Assessing the Potential of Gel–SA–MgHA Composite Biomaterial Ink for 3D Bioprinting Tracheal Stents

  ChemistrySelect · 2025-01-01

  articleOpen access

  Abstract Diseases such as injury, stenosis, and tumors of the long trachea usually require the removal of the affected part of the trachea. There is an urgent need to implant tracheal stents as substitutes in clinical practice. In this paper, Mg 2+ was first doped into hydroxyapatite (HA) matrix by hydrothermal synthesis and then mixed with gelatin sodium alginate (Gel–SA) double network crosslinked hydrogel to prepare gelatin sodium alginate magnesium doped hydroxyapatite (Gel–SA–MgHA) composite biomaterial ink. The trachea stent was prepared by 3D bioprinting technology and its physicochemical, mechanical, and biological properties were systematically evaluated. Due to the large number of hydrophilic groups on the surface of the HA matrix, the addition of MgHA improved the hydrophilicity of tracheal stents. The mechanical properties of the stent first increase and then decrease with the increase of MgHA content. When the MgHA content is 4 wt%, the tracheal stent has the optimal mechanical properties. In vitro cytology experiments have confirmed that the four stent materials have good cell compatibility and proliferation characteristics. Overall, Gel–SA–4MgHA has the best mechanical and cytological properties, and has certain potential in the clinical application of tracheal stents.

  PublisherOA PDFDOI

• Enhanced phosphorus elimination from aquatic systems employing modified granular waterworks derived sludge composite materials: Mechanistic evaluation and process optimization

  PLoS ONE · 2025-10-31

  articleOpen accessCorresponding

  A novel granular waterworks-derived sludge composite (GT La-WDS) was synthesized via green and low-carbon hydrothermal carbonization combined with a calcination-free granulation method, demonstrating exceptional phosphate adsorption performance and potential as constructed wetland filler. Comprehensive characterization (SEM, XRF, BET, FTIR, XRD) revealed its hierarchical porous morphology, chemical composition, and hydroxyl/ligand-functionalized surfaces. Optimal phosphate adsorption capacity (20.11 mg/g) was achieved at pH 4, with adsorption mechanisms dominated by ligand substitution and formation of inner-sphere complexes, as supported by quasi-second-order kinetic modeling and Freundlich isotherm conformity. Dynamic column tests showed prolonged breakthrough (from 168 h to 432 h) and exhaustion times (from 588 h to 2088 h) with increasing bed heights (10 cm to 30 cm), achieving total adsorption capacities of 9.276 mg/g. Effluent phosphate concentrations remained below 0.5 mg/L (Chinese National Effluent Standard Class 1B) for 588 h, with sustained removal efficiency over 2088 h, indicating remarkable longevity. This sludge-derived composite presents a cost-effective solution for phosphorus sequestration, offering dual benefits of eutrophication mitigation and sustainable sludge valorization, with particular relevance to low-carbon constructed wetland systems.

  PublisherDOI

• Application Potential of <scp>UHMWPE</scp> Based Composite Materials With <scp>MWCNTs</scp> and <scp>ZnO</scp> Addition in Acetabular Cup Prostheses

  Journal of Applied Polymer Science · 2025-02-18

  articleCorresponding

  ABSTRACT In order to improve the wear and aging resistance of UHMWPE based polymer acetabular cup prosthesis, the hot‐embossing method is used to prepare multi‐component MWCNTs/ZnO added UHMWPE based composite materials in this article. The research results found that the diffusion characteristics of MWCNTs/ZnO additives in composite materials have a significant impact on their wear resistance. Under the condition of 25% NBS, the wear rate of the UMZ‐3 sample was 13.94% lower than that of the pure U sample. Although MWCNTs can play a role in reducing friction to a certain extent, their high hardness characteristics may lead to the release of the composite material as a third body during friction. The optimization of heat transfer performance of MWCNTs/ZnO composite materials has alleviated the aging process to a certain extent and suppressed the softening phenomenon. Compared with the OI value of the pure U sample, which is in the range of 1.4–5.1, the OI value of the UMZ‐3 sample is in the range of 2.62–3.06. In addition, the synergistic effect of MWCNTs/ZnO effectively inhibits the oxidation process while also having a positive impact on cell proliferation, demonstrating its potential as an additive to enhance the service life of polymer acetabular cups.

  PublisherDOI

• An Analysis of the Impact of Digital Transformation on Corporate ESG Performance

  Advances in Economics Management and Political Sciences · 2025-05-30

  articleOpen accessSenior author

  This paper employs textual analysis and empirical data from the Wind Financial Terminal (CSMAR database) to investigate how digital transformation influences corporate ESG performance through the mediating roles of green innovation capability and total factor productivity. The findings reveal that digital transformation optimizes resource allocation and promotes green technological innovation, thereby enhancing environmental performance. At the same time, it improves production efficiency and resource utilization, strengthens corporate social responsibility fulfillment and governance capabilities, and significantly enhances overall ESG performance. This study provides a theoretical basis for corporate practices.

  PublisherOA PDFDOI

• Sociodemographically differential patterns of chronic pain progression revealed by analyzing the all of us research program data

  PLOS Digital Health · 2025-06-17 · 1 citations

  articleOpen accessSenior author

  The differential progression of ten chronic overlapping pain conditions (COPC) and four comorbid mental disorders across demographic groups have rarely been reported in the literature. To fill in this gap, we conducted retrospective cohort analyses using All of Us Research Program data from 1970 to 2023. Separate cohorts were created to assess the differential patterns across sex, race, and ethnicity. Logistic regression models, controlling for demographic variables and household income level, were employed to identify significant sociodemographic factors associated with the differential progression from one COPC or mental condition to another. Among the 139 frequent disease pairs, we identified group-specific patterns in 15 progression pathways. Black or African Americans with a COPC condition had a significantly increased association in progression to other COPCs (CLBP- > IBS, CLBP- > MHA, or IBS- > MHA, OR≥1.25, adj.p ≤ 4.0x10-3) or mental disorders (CLBP- > anxiety, CLBP- > depression, MHA- > anxiety, MHA- > depression, OR≥1.25, adj.p ≤ 1.9x10-2) after developing a COPC. Females had an increased likelihood of chronic low back pain after anxiety and depression (OR≥1.12, adj.p ≤ 1.5x10-2). Additionally, the lowest income bracket was associated with an increased risk of developing another COPC from a COPC (CLBP- > MHA, IBS- > MHA, MHA- > CLBP, or MHA- > IBS, OR≥1.44, adj.p ≤ 2.6x10-2) or from a mental disorder (depression- > MHA, depression- > CLBP, anxiety- > CLBP, or anxiety- > IBS, OR≥1.50, adj.p ≤ 2.0x10-2), as well as developing a mental disorder after a COPC (CLBP- > depression, CBLP- > anxiety, MHA- > anxiety, OR≥1.37,adj.p ≤ 1.6x10-2). To our knowledge, this is the first study that unveils the sociodemographic influence on COPC progression. These findings suggest the importance of considering sociodemographic factors to achieve optimal prognostication and preemptive management of COPCs.

  PublisherDOI

• Association between relative surface temperature and urban park visits during excessive heat

  Environmental Research Communications · 2025-06-01 · 2 citations

  articleOpen access1st authorCorresponding

  Abstract Parks provide essential services for urban residents. In arid/semi-arid regions and urban areas in general, frequent extreme heat events and prolonged heat waves are threatening people’s visits and use of parks. A variety of heat indicators have been developed in the literature. Prior studies on the impact of thermal environments on park usage rarely examined the associations between site-level heat indicators and park visits and usage behaviors. In this study, we assess the impacts of heat on park visits and usage and identify site-level heat indicators that are significantly associated with individual park use behaviors. We combined in situ temperature measurements with observational data, employing a generalized linear mixed-effects model with a negative binomial distribution to identify associations between heat-related factors and park usage. The results show that relative surface temperature is negatively correlated with park visits in all seasons (coefficient −0.02, p &lt;0.001) after controlling for other confounding factors. The study suggests that relative surface temperature may be a promising metric for assessing the microenvironments of parks exposed to heat and the impact of temperature on park visits and usage. This study provides valuable insights for guiding park design and management, with potential benefits for community health and well-being.

  PublisherDOI

• Under the background of the new global definition of ARDS: an interpretable machine learning approach for predicting 28-day ICU mortality in patients with sepsis complicated by ARDS

  Frontiers in Physiology · 2025-09-19 · 3 citations

  articleOpen accessCorresponding

  Background: Acute respiratory distress syndrome (ARDS) is a prevalent clinical complication among patients with sepsis, characterized by high incidence and mortality rates. The definition of ARDS has evolved over time, with the new global definition introducing significant updates to its diagnosis and treatment. Our objective is to develop and validate an interpretable prediction model for the prognosis of sepsis patients complicated by ARDS, utilizing machine learning techniques in accordance with the new global definition. Methods: This study extracted data from the MIMIC database (version MIMIC-IV 2.2) to create the training set for our model. For external validation, this study used data from sepsis patients complicated by ARDS who met the new global definition of ARDS, sourced from the Affiliated Hospital of Xuzhou Medical University. Lasso regression with cross-validation was used to identify key predictors of patient prognosis. Subsequently, this study established models to predict the 28-day prognosis following ICU admission using various machine learning algorithms, including logistic regression, random forest, decision tree, support vector machine classifier, LightGBM, XGBoost, AdaBoost, and multi-layer perceptron (MLP). Model performance was assessed using ROC curves, clinical decision curves (DCA), and calibration curves, while SHAP values were utilized to interpret the machine learning models. Results: A total of 905 patients with sepsis complicated by ARDS were included in our analysis, leading to the selection of 15 key variables for model development. Based on the AUC of the ROC curve, as well as DCA and calibration curve results from the training set, the support vector classifier (SVC) model demonstrated strong performance, achieving an average AUC of 0.792 in the internal validation set and 0.816 in the external validation set. Conclusion: The application of machine learning methodologies to construct prognostic prediction models for sepsis patients complicated by ARDS, informed by the new global definition, proves to be reliable. This approach can assist clinicians in developing personalized treatment strategies for affected patients.

  PublisherOA PDFDOI

Frequent coauthors

• Yves A. Lussier

  University of Utah

  75 shared

• Periannan Kuppusamy

  35 shared

• Jay L. Zweíer

  The Ohio State University

  33 shared

• Govindasamy Ilangovan

  Lung Institute

  26 shared

• Colleen Kenost

  University of Utah

  21 shared

• Jianrong Li

  21 shared

• Jie Zhao

  Institute of Hematology & Blood Diseases Hospital

  19 shared

• Ikbel Achour

  18 shared