About

Zhe Lu, MD, PhD, is a Professor of Physiology at the University of Pennsylvania's Perelman School of Medicine. He received his M.D. from Beijing Medical University in 1986, and completed his M.S. and Ph.D. in Physiology at the University of Wisconsin in 1989 and 1992, respectively. His research focuses on the fundamental mechanisms of ion channels and the pathogenesis of ion channel-based genetic diseases such as cystic fibrosis and diabetes. His laboratory investigates how ion channels, including potassium channels, cGMP-gated cation channels, and the cystic fibrosis conductance regulator chloride channel, function and are regulated by cell signaling systems. The research aims to develop novel pharmacological agents to control ion channel activity and to understand the molecular mechanisms underlying channelopathies. Dr. Lu's work employs structural and functional approaches, including electrophysiological techniques, membrane protein crystallography, and molecular biology, to elucidate ion channel mechanisms and develop targeted inhibitors. His contributions include advancing knowledge on ion channel structure-function relationships and their roles in electrical signaling in nerve, muscle, and endocrine cells.

Research topics

• Biochemistry
• Chemistry
• Biology
• Immunology
• Cancer research
• Internal medicine
• Endocrinology
• Medicine

Selected publications

• Sharing electronic and ionic transfer channels for high-energy-density and stable quasi-solid-state lithium-oxygen battery

  National Science Review · 2026-03-03

  articleOpen access

  Abstract Thick cathodes are essential for practical high-energy batteries, yet their development is hindered by sluggish charge kinetics, particularly in lithium-oxygen batteries (LOBs) where robust three-phase boundaries (TPBs) for e−, Li+, and O2 are indispensable. Herein, we propose a gel polymer electrolyte (GPE) integration strategy that enables the construction of a streamlined dual-conductive network for both e− and Li+ while preserving optimal porosity for rapid O2 diffusion in thick cathodes (~2 mm). This innovative architecture creates extensive and continuous TPBs throughout the entire cathode, enabling an exceptional areal capacity of 34.6 mAh cm−2, surpassing most previously reported LOBs, and a record-breaking gravimetric capacity of 19000 mAh g−1. Numerical simulations further validate the superiority of this approach. Our work provides a proof of concept for overcoming kinetic transport limitations in thick cathodes, paving the way for next-generation high-capacity and stable LOBs.

  PublisherDOI

• Advances in the Characteristics of Fibroblasts in Keloid: A Review

  Experimental Dermatology · 2026-03-01

  articleSenior authorCorresponding

  Keloids (KDs) are a group of fibroproliferative skin diseases characterised by an excess of fibroblasts and the accumulation of extracellular matrix (ECM). In KDs, keloid fibroblasts (KFs) serve as the primary effector cells, playing a pivotal role. By studying the signalling pathways and epigenetic changes of KFs, researchers can elucidate the mechanisms behind the formation of KDs. This understanding is crucial for identifying potential targets for innovative treatments. In this paper, we review the latest progress in KFs research, detailing their abnormal biological characteristics, with some special KFs subgroups deserving particular attention. We also discuss the aberrantly regulated signalling pathways and therapeutic approaches concerning KFs, aiming to provide insights into the pathogenesis of keloid scars and thereby guide future research directions.

  PublisherDOI

• Rab14 restricts pathogens by promoting V-ATPase lysosomal delivery to drive lysosomal acidification

  Nature Communications · 2026-03-02

  articleOpen access

  Host restriction factors mediate intrinsic immunity against infections, thus serving as promising targets for host-directed therapy (HDT) against drug-resistant pathogens. While restriction factors counteracting viruses have been extensively studied, those targeting bacteria, particularly those with broad-spectrum activity, remain largely unexplored. Here, through screening for host factors promoting lysosomal acidification, a crucial process clearing pathogens, we identify the host small GTPase Rab14 as a restriction factor with broad-spectrum activity against multiple bacteria and viruses. Mechanistically, upon pathogen infections, GTP-bound Rab14 increases and binds to the calcium/calmodulin-dependent protein kinase type 2 delta (CAMK2D), suppressing CAMK2D-mediated phosphorylation of V0a1, the critical subunit determining V-ATPase localization, thus promoting V0a1 binding to the COPⅡ complex to facilitate V-ATPase trafficking from the endoplasmic reticulum to lysosomes, resulting in lysosomal acidification and pathogen clearance. Taken together, our data demonstrate an unrecognized intrinsic immune mechanism mediated by Rab14-CAMK2D-V-ATPase axis, which might be a promising target for infectious diseases. Broad-spectrum host restriction factors against bacteria and viruses remain largely unclear. Here, the authors identify the small GTPase Rab14 as a restriction factor that promotes lysosomal acidification by delivering the V-ATPase to lysosomes.

  PublisherOA PDFDOI

• Ag Doping Modulating Cathode Acidic Sites to Enhance Chromium Resistance for Intermediate Temperature Solid Oxide Fuel Cells

  Journal of Inorganic Materials · 2025-05-22

  articleOpen access
  PublisherOA PDFDOI

• Examination of conformational dynamics of AdiC transporter with fluorescence-polarization microscopy

  The Journal of General Physiology · 2025-01-20 · 2 citations

  articleOpen accessSenior author

  To understand the mechanism underlying the ability of individual AdiC molecules to transport arginine and agmatine, we used a recently developed high-resolution single-molecule fluorescence-polarization microscopy method to investigate conformation-specific changes in the emission polarization of a bifunctional fluorophore attached to an AdiC molecule. With this capability, we resolved AdiC's four conformations characterized by distinct spatial orientations in the absence or presence of the two substrates, and furthermore, each conformation's two energetic states, totaling 24 states. From the lifetimes of individual states and state-to-state transition probabilities, we determined 60 rate constants characterizing the transitions and 4 KD values characterizing the interactions of AdiC's two sides with arginine and agmatine, quantitatively defining a 24-state model. This model satisfactorily predicts the observed Michaelis-Menten behaviors of AdiC. With the acquired temporal information and existing structural information, we illustrated how to build an experiment-based integrative 4D model to capture and exhibit the complex spatiotemporal mechanisms underlying facilitated transport of substrates. However, inconsistent with what is expected from the prevailing hypothesis that AdiC is a 1:1 exchanger, all observed conformations transitioned among themselves with or without the presence of substrates. To corroborate this unexpected finding, we performed radioactive flux assays and found that the results are also incompatible with the hypothesis. As a technical advance, we showed that a monofunctional and the standard bifunctional fluorophore labels report comparable spatial orientation information defined in a local frame of reference. Here, the successful determination of the complex conformation-kinetic mechanism of AdiC demonstrates the unprecedented resolving power of the present microscopy method.

  PublisherDOI

• Characterization and structural basis for the brightness of mCLIFY: A novel monomeric and circularly permuted bright yellow fluorescent protein

  Biophysical Journal · 2025-05-22

  article
  PublisherDOI

• Utilizing AI models to identify and predict phase transition patterns of bipolar disorder patients

  Journal Of Big Data · 2025-04-24 · 2 citations

  articleOpen access

  This study employs artificial intelligence methods to predict mood phases in patients with bipolar disorder, addressing the issue of poor prognosis caused by recurrent episodes and uncertainty in mood phases. To explore the patterns of mood transitions in patients with bipolar disorder, we developed a mood phase transition model using a Transformer model to investigate whether predicting mood changes can improve prognosis. We conducted cohort follow-up assessments of patients with bipolar disorder. At each visit, patients were evaluated using the Hamilton Depression Rating Scale (HAMD) and the Young Mania Rating Scale (YMRS) as clinician-rated assessments, along with the BDCC self-rating scale. We then input these data into several different AI models for training and validated the models’ performance using the data. The study was conducted through online medical platforms and offline follow-up evaluations. The study included 812 patients diagnosed with bipolar disorder according to DSM-5 criteria, who had at least one BDCC assessment result and at least one depressive episode meeting HAMD criteria and one manic/hypomanic episode meeting YMRS criteria. In the experiment utilizing current self-assessment scales for rapid identification of affective states, the best performance was observed with the Transformer and RF models, with AUCs for affective state identification of 0.83 (95% CI 0.77–0.89) for the Transformer model, and 0.88 (95% CI 0.83–0.93) for the RF model. In experiments predicting the next affective state, the AUC for the Transformer prediction was 0.76 (95% CI 0.65–0.87), and for the RF model, it was 0.78 (95% CI 0.68–0.88). In predictions of affective states 90 days later, the Transformer model performed best, with accuracies of 82.76%, 79.31%, 58.62%, and 41.38% for the Transformer, CNN, RF, and SVM models, respectively. To some extent, the AI model can predict patients’ mood phase transition patterns, achieving an AUC greater than 0.8. Decision Curve Analysis (DCA) indicates that patients may obtain clinical benefits based on this predictive model. Additionally, the model demonstrates optimal predictive performance at 180 days. http://ClinicalTrials.gov under the identifier NCT02015143

  PublisherOA PDFDOI

• Characterization and Structural Basis for the Brightness of mCLIFY: A Novel Monomeric and Circularly Permuted Bright Yellow Fluorescent Protein

  Research Square · 2024-07-19 · 1 citations

  preprintOpen access
  PublisherOA PDFDOI

• Structural determinants of the enhanced photophysical properties of the fluorescent yellow protein mCLIFY

  Biophysical Journal · 2024-02-01

  articleOpen access
  PublisherOA PDFDOI

• Multiple Functional Variants and Genes at a Single Locus for Alzheimer’s Disease

  Biological Psychiatry · 2023-09-29 · 2 citations

  letter1st author
  PublisherDOI

Recent grants

• Angstrom-scale structural dynamics of a potassium channel

  NIH · $9.1M · 1997–2026

• NIH Grant R01GM061929

  NIH · $2.3M · 2011

• NIH Grant K02HL003814

  NIH · $488k · 2003

• Development of novel means to stimulate Ca2+-dependent exocytotic secretion

  NIH · $1.6M · 2016–2020

Frequent coauthors

• Yanping Xu

  Ningxia Medical University

  40 shared

• Yajamana Ramu

  25 shared

• Hyeon-Gyu Shin

  22 shared

• Juan Ramón Martínez‐François

  Harvard University

  12 shared

• George F. Gao

  12 shared

• John H. Lewis

  Educational Testing Service

  10 shared

• David J. Combs

  10 shared

• Szilvia Szép

  8 shared

Labs

• Zhe Lu LaboratoryPI

Education

• M.D.

  Beijing Medical University

  1986

• M.S., Physiology

  University of Wisconsin

  1989

• Ph.D., Physiology

  University of Wisconsin

  1992