Biology subjects

Guo, C.

Publications and source records attributed to Guo, C..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

CalTrig: A GUI-Based Machine Learning Approach for Decoding Neuronal Calcium Transients in Freely Moving Rodents

Advances in in vivo Ca2+ imaging using miniature microscopes have enabled researchers to study single-neuron activity in freely-moving animals. Tools such as MiniAN and CalmAn have been developed to convert Ca2+ visual signals to numerical data, collectively referred to as CalV2N. However, substantial challenges remain in analyzing the large datasets generated by CalV2N, particularly in integrating data streams, evaluating CalV2N output quality, and reliably and efficiently identifying Ca2+ transients. In this study, we introduce CalTrig, an open-source graphical user interface (GUI) tool designed to address these challenges at the post-CalV2N stage of data processing. CalTrig integrates multiple data streams, including Ca2+ imaging, neuronal footprints, Ca2+ traces, and behavioral tracking, and offers capabilities for evaluating the quality of CalV2N outputs. It enables synchronized visualization and efficient Ca2+ transient identification. We evaluated four machine learning models (i.e., GRU, LSTM, Transformer, and Local Transformer) for Ca2+ transient detection. Our results indicate that the GRU model offers the highest predictability and computational efficiency, achieving stable performance across training sessions, different animals and even among different brain regions. The integration of manual, parameter-based, and machine learning-based detection methods in CalTrig provides flexibility and accuracy for various research applications. The user-friendly interface and low computing demands of CalTrig make it accessible to neuroscientists without programming expertise. We further conclude that CalTrig enables deeper exploration of brain function, supports hypothesis generation about neuronal mechanisms, and opens new avenues for understanding neurological disorders and developing treatments.

neuroscience↗

bioRxiv2024

An all-in-one AAV vector for cardiac-specific gene silencing by an adenine base editor

ABE editing outcomes are highly variable and unpredictable, depending on various factors. Therefore, the success rate of creating targeted A*T-to-G*C conversions using ABE is not high. But utilizing ABE to target RNA splicing sites for gene silencing has a higher success rate. Another challenge for base editing in the heart is that traditional ABE is too large in size, necessitating dual AAV delivery. Whether single AAV delivery can be achieved remains to be explored. In this study, we demonstrated how the diversity of Cas9 homologs and screening of sgRNAs can facilitate cardiac base editing. Single-AAV base editing outperformed dual-AAV systems in the heart, potentially benefiting from chromatin accessibility-guided sgRNA selection. These findings have important implications for the development of more effective and predictable base editing tools for cardiac gene therapy.

molecular biology↗

bioRxiv2024

Novel derivatives of BCV and (S)-HPMPA inhibit orthopoxviruses and human adenoviruses more potently than BCV

BCV and tecovirimat are the only two chemical drugs that have been approved to treat smallpox and can be requested for Mpox treatment through a single-patient Emergency Investigational New Drug (EIND) application. Disappointedly, the efficacy of tecovirimat manifested in a recent clinical trial is far from being satisfactory, while the clinical efficacy of BCV is still inconclusive. Given that MPXV, variola and other emerging orthopoxviruses are posing serious threats to global health, it is urgent to develop better therapeutics. In this study, we tested the antiviral effects of three novel prodrugs, which were designed based on previously reported parent drugs, either (S)-HPMPC (cidofovir) or (S)-HPMPA. We found that one of the (S)-HPMPA-based prodrugs, ODE-(S)-HPMPA formate, exhibited significantly better anti-orthopoxvirus activity than BCV both in vitro and in vivo, which also inhibited human adenovirus type 2 and type 21 more efficiently than BCV. Most strikingly, the EC50 and EC90 of ODE-(S)-HPMPA formate against MPXV were more than 40-fold lower than those of BCV. In contrast, we observed that the anti-HSV-1 activities of the (S)-HPMPA-based prodrugs were less effective than those of the cidofovir-based prodrugs (BCV and BCV formate), especially in vivo. Moreover, we showed for the first time that cytidine and adenine analog combined therapies could provide mice with complete protection against lethal challenges of both vaccinia and HSV-1. Collectively, we propose that both the ODE-(S)-HPMPA formate and the BCV/ODE-(S)-HPMPA formate combination are worth further investigations for their potential clinical applications.

microbiology↗

bioRxiv2024

MiniXL: An open-source, large field-of-view epifluorescence miniature microscope for mice capable of single-cell resolution and multi-brain region imaging

Capturing the intricate dynamics of neural activity in freely behaving animals is essential for understanding the neural mechanisms underpinning specific behaviors. Miniaturized microscopy enables investigators to track population activity at cellular level, but the field of view (FOV) of these microscopes have been limited and does not allow multiple-brain region imaging. To fill this technological gap, we have developed the eXtra Large field-of-view Miniscope (MiniXL), a 3.5g lightweight miniaturized microscope with an FOV measuring 3.5 mm in diameter and an electrically adjustable working distance of 1.9 mm {+/-} 200 m. We demonstrated the capability of MiniXL recording the activity of large neuronal population in both subcortical area (hippocampal dorsal CA1) and deep brain regions (medial prefrontal cortex, mPFC and nucleus accumbens, NAc). The large FOV allows simultaneous imaging of multiple brain regions such as bilateral mPFCs or mPFC and NAc during complex social behavior and tracking cells across multiple sessions. As with all microscopes in the UCLA Miniscope ecosystem, the MiniXL is fully open-source and will be shared with the neuroscience community to lower the barriers for adoption of this technology.

neuroscience↗

bioRxiv2024

Lung Microbiome Intervention Attenuates Herpesvirus-Induced Post-HCT Pulmonary Fibrosis Through PD-L1 Upregulation on Dendritic Cells

Alterations in the lung microbiome frequently accompany adverse pulmonary outcomes. Hematopoietic cell transplantation (HCT) markedly affects the lung microbiome corresponding with a high incidence of post-HCT pulmonary complications. In a preclinical mouse model of HCT, we observed a reduction in Lactobacillus johnsonii within the lung microbiome following transplantation. Intranasal administration of live or heat-killed (HK) L. johnsonii at low doses reduced gammaherpesvirus-induced pulmonary fibrosis in HCT mice, in which IL-17A plays an essential role. HK L. johnsonii treatment of HCT mice suppressed inflammatory cytokine production by lung macrophages and decreased Il17a expression in T helper 17 (Th17) cells. HK L. johnsonii increased PD-L1 expression on the surface of type II conventional dendritic cells (cDC2) in HCT mice and in vitro in bone marrow-derived dendritic cells (BMDCs). HK L. johnsonii-exposed BMDCs also inhibited IL-17A secretion from co-cultured Th17 cells in a PD-1-dependent manner. Notably, when HK L. johnsonii was administered to HCT mice reconstituted with bone marrow cells from PD-1 knockout (KO) mice, which lack a PD-L1 mediated response, HK L. johnsonii-mediated reduction of pulmonary fibrosis was negated. Collectively, our findings demonstrate that HK L. johnsonii mitigates herpesvirus-induced pulmonary fibrosis in HCT mice by modulating cDC2 surface expression of PD-L1, which subsequently suppresses Il17a expression in Th17 cells, pointing towards a potential postbiotic-based strategy for immunomodulation to address pulmonary complications of HCT.

immunology↗

bioRxiv2024

Fibrillarin modulates fetal hemoglobin silencing

Decoding the molecular mechanisms underlying human fetal ({gamma}) globin gene silencing impacts therapeutic strategies for {beta}-thalassemia and sickle cell disease. Here, we identified a nucleolar protein, fibrillarin (FBL), which mediates the methylation of glutamine104 in histone H2A and functions as a repressor of the {gamma}-globin gene in cultured erythroid cells, including those from {beta}-thalassemia patients. Conditional Fbl depletion in adult {beta}-YAC transgenic mice or in {beta}IVS-2-654-thalassemic mice reactivated the human {gamma}-globin gene or murine embryonic globin expression, respectively, which corrects hematologic and pathologic defects in {beta}-thalassemic mice. We showed that FBL plays a dual role in activating BCL11A expression and repressing {gamma}-globin gene expression, which is dependent on its histone methyltransferase activity. Our study may provide an alternative strategy for therapeutic targeted treatment of {beta}-hemoglobinopathies.

molecular biology↗

bioRxiv2024

Intra-genomic genes-to-genes correlation enables genome representaion

The bacterial pan-genome consists of core genes shared by all members of a taxonomy and accessory genes found in only a subset. The correlation among genes within the pan-genome could advance our understanding of evolution and tackle medical challenges. Here, we discovered a strong intra-genomic correlation among bacterial pan-genes within each of Escherichia coli, Listeria monocytogenes, Staphylococcus aureus, and Campylobacter jejuni. With a convolutional neural network assisted core genome knock-out simulation, we found that different combinations of fewer than 20 highly variable core genes could recover the sub-species type classified by complete core genome with accuracy >95%. This observation led us to test the genes-to-genes predictability: with more than 52,000 assemblies from each species, combinations of highly variable core genes could predict the sequence variants of other core genes (average accuracy >94%) within the same genome and could also predict sequence variants (average accuracy >91%) as well as the presence (average AUROC >0.91) of some accessory genes. Furthermore, combinations of highly variable core genes could also predict multiple antibiotic resistances (AUROC >0.80) in large published datasets of E. coli, S. aureus, and Mycobacterium tuberculosis. Collectively, we propose that genes within the same genome can strongly correlate with each other. Therefore, the strain phylogeny and the status of other genes could be uniformly represented by combinations of highly variable core genes, which could further represent certain phenotypes including in vitro resistance.

bioinformatics↗

bioRxiv2024

Cyclic di-GMP as an Antitoxin Regulates Bacterial Genome Stability and Antibiotic Persistence in Biofilms

Biofilms are complex bacterial communities characterized by a high persister prevalence, which contributes to chronic and relapsing infections. Historically, persister formation in biofilms has been linked to constraints imposed by their dense structures. However, we observed an elevated persister frequency accompanying the stage of cell adhesion, marking the onset of biofilm development. Subsequent mechanistic studies uncovered a comparable type of toxin-antitoxin (TA) module (TA-like system) triggered by cell adhesion, which is responsible for this elevation. In this module, the toxin HipH acts as a genotoxic deoxyribonuclease, inducing DNA double strand breaks and genome instability. While the second messenger c-di-GMP functions as the antitoxin, exerting control over HipH expression and activity. The dynamic interplay between c-di-GMP and HipH levels emerges as a crucial determinant governing genome stability and persister generation within biofilms. These findings unveil a unique TA system, where small molecules act as the antitoxin, outlining a biofilm-specific molecular mechanism influencing genome stability and antibiotic persistence, with potential implications for treating biofilm infections.

microbiology↗

bioRxiv2024

Decoding the Role of Secondary Motor Cortex Neuronal Ensembles during Cocaine Self-Administration: Insights from Longitudinal in vivo Calcium Imaging via Miniscopes

BackgroundWe recently reported that the risk of cocaine relapse is linked to hyperexcitability in the secondary motor cortex (M2) after prolonged withdrawal following intravenous self-administration (IVSA). However, the neuronal mechanisms underlying drug-taking behaviors and the response of M2 neurons to contingent drug delivery remain poorly understood. MethodsMice received cocaine as reinforcement (RNF) following active lever presses (ALP) but not inactive lever presses (ILP). Using in vivo calcium imaging during cocaine IVSA, we tracked M2 neuronal activity with single-cell resolution. We then analyzed Ca2+ transients in M2 at the early vs. late stages during the 1-hr daily sessions on IVSA Day 1 and Day 5. ResultsM2 neurons adapted to both operant behaviors and drug exposure history. Specifically, saline mice showed a reduction in both saline taking behaviors and Ca2+ transient frequency with the 1-hr session. In contrast, cocaine mice maintained high ALP and RNF counts, with increased Ca2+ transient frequency and amplitude on Day 1, persisting through Day 5. Compared to saline controls, cocaine mice exhibited a lower % of positively responsive neurons (Pos) and higher % of negatively responsive neurons (Neg) before ALP and after RNF, a difference not seen before ILP. Furthermore, as drug-taking behaviors progressed during the daily session, cocaine mice showed greater neuronal engagement with a larger population, particularly linked to ALP and RNF, with reduced overlap in neurons associated with ILP. ConclusionThe M2 undergoes dynamic neuronal adaptations during early drug-taking behaviors, indicating its role as a potential substrate mediating the persistence of drug-seeking behaviors in cocaine relapse.

neuroscience↗

bioRxiv2024

Propofol overcome Tamoxifen resistance in breast cancer by modulating tumorogenesis, immune response and metabolism

Although 70% of estrogen receptor (ER)-positive breast cancer patients benefit from Tamoxifen therapy, the developing resistance to Tamoxifen leads to high rates of metastasis and poor prognosis. Propofol, a commonly used anesthetic, has been shown to inhibit the occurrence and development of breast cancer. However, its role in anti-endocrine resistance in ER-positive breast cancer remains unclear. In this study, we found that Propofol significantly promotes cell cycle arrest, induces apoptosis, and inhibits proliferation in Tamoxifen-resistant breast cancer cells. Furthermore, transcriptome sequencing analysis revealed 1065 differentially expressed genes (DEGs) between Propofol-treated Tamoxifen-resistant MCF-7 (MCF7-TR) cells and none-treated MCF7-TR cells. Gene ontology annotation enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis (KEGG), and gene set enrichment analysis (GSEA) showed that Propofol affects the expression of genes located in the plasma membrane and cell periphery, mainly regulating signals involved in cell cycle regulation, immune response modulation, and metabolism. Our results provide new insights into the mechanism by which Propofol controls resistance to Tamoxifen in breast cancer progression and offer a theoretical basis for clinical treatment.

cancer biology↗

bioRxiv2024

Development of a Two-Leaf Photosynthetic Model Sensitive to Chlorophyll and Its Coupling with a Wheat Growth Model

Crop growth models (CGMs) commonly simulates the response of photosynthetic rate to nitrogen (N) dynamic by calculating critical N concentration. However, critical N concentration makes it hard to describe the physiological effect of N dynamic on photosynthesis. Meanwhile, the effect of diffuse light on photosynthesis was limited in previous studies. In this study, we introduced a Two-leaf Photosynthetic Model Sensitive to Chlorophyll Content (TPMSCC) and coupled it with the crop growth model (WheatGrow) to enhance our understanding of how N dynamic and diffuse light affects photosynthesis. By coupling the Farquhar-von Caemmerer-Berry (FvCB) C3 photosynthesis model with a canopy radiative transfer model (PROSAIL), TPMSCC simulated the light interception of direct and diffuse light, and employed leaf chlorophyll content (LCC) to simulate the light absorption and electron transfer rate of leaves. Result showed that TPMSCC well simulated the light absorption of the wheat canopy and found the canopy photosynthetic rate benefited from the increase of diffuse radiation fraction (DRF) except for when the condition of a dense canopy at a high solar zenith angle was present. Research found the logarithmic and linear relationships of LCC to the initial light use efficiency ([a]) and the maximum photosynthetic rate (Amax), respectively, which followed the field measurements. Additionally, the optimized WheatGrow model outperforms its predecessor in describing the response of N application rate on photosynthesis.

biophysics↗

bioRxiv2024

Stimulated Prorocentrum donghaiense cell growth by in-situ mariculture dissolved organic matter

Mixotrophic dinoflagellates frequently cause harmful algal blooms (HAB) in eutrophic mariculture waters that contain diverse excreted dissolved organic matter (DOM). The phagotrophy and the utilization of single organic small molecules have been extensively investigated in the bloom-forming mixotrophic dinoflagellates. However, their ability to utilize the in-situ DOM via absorbtrophy still remains unexplored. Here we examined the growth promotion effect of the in-situ mariculture DOM on Prorocentrum donghaiense, a representative HAB-forming species in coastal waters. Our results showed that the cell growth and photosynthesis of P. donghaiense were significantly promoted under in-situ DOM culture conditions. Additionally, parallel cultures were set up to disclose the potential role of the bacterioplankton in the free-living community (helper), where they aid in the remineralization of the in-situ DOM, and the phycosphere community (competitor), where they compete against the algal host to acquire nutrients from the in-situ DOM. Meanwhile, we determined the cellular stoichiometry under different culture conditions, showing that mariculture DOM can shape cellular stoichiometry significantly. Elevated cellular N (84.96%) and P (48.3%) were observed in spring DOM groups compared with the control groups. For the first time, this study quantifies the efficient utilization of the in-situ DOM via absorbtrophy, indicating the vital role in the outbreak and maintenance of HAB events.

ecology↗

bioRxiv2024

Self-inspired learning to denoise for live-cell super-resolution microscopy

Every collected photon is precious in live-cell super-resolution (SR) fluorescence microscopy for contributing to breaking the diffraction limit with the preservation of temporal resolvability. Here, to maximize the utilization of accumulated photons, we propose SN2N, a Self-inspired Noise2Noise engine with self-supervised data generation and self-constrained learning process, which is an effective and data-efficient learning-based denoising solution for high-quality SR imaging in general. Through simulations and experiments, we show that the SN2Ns performance is fully competitive to the supervised learning methods but circumventing the need for large training-set and clean ground-truth, in which a single noisy frame is feasible for training. By one-to-two orders of magnitude increased photon efficiency, the direct applications on various confocal-based SR systems highlight the versatility of SN2N for allowing fast and gentle 5D SR imaging. We also integrated SN2N into the prevailing SR reconstructions for artifacts removal, enabling efficient reconstructions from limited photons. Together, we anticipate our SN2N and its integrations could inspire further advances in the rapidly developing field of fluorescence imaging and benefit subsequent precise structure segmentation irrespective of noise conditions.

bioengineering↗

bioRxiv2024

TDP-43 nuclear loss in FTD/ALS causes widespread alternative polyadenylation changes

In frontotemporal dementia and amyotrophic lateral sclerosis, the RNA-binding protein TDP-43 is depleted from the nucleus. TDP-43 loss leads to cryptic exon inclusion but a role in other RNA processing events remains unresolved. Here, we show that loss of TDP-43 causes widespread changes in alternative polyadenylation, impacting expression of disease-relevant genes (e.g., ELP1, NEFL, and TMEM106B) and providing evidence that alternative polyadenylation is a new facet of TDP-43 pathology.

neuroscience↗

bioRxiv2024

Antigen-display exosomes provide adjuvant-free protection against SARS-CoV-2 disease at nanogram levels of spike protein

As the only bionormal nanovesicle, exosomes have high potential as a nanovesicle for delivering vaccines and therapeutics. We show here that the loading of type-1 membrane proteins into the exosome membrane is induced by exosome membrane anchor domains, EMADs, that maximize protein delivery to the plasma membrane, minimize protein sorting to other compartments, and direct proteins into exosome membranes. Using SARS-CoV-2 spike as an example and EMAD13 as our most effective exosome membrane anchor, we show that cells expressing a spike-EMAD13 fusion protein produced exosomes that carry dense arrays of spike trimers on 50% of all exosomes. Moreover, we find that immunization with spike-EMAD13 exosomes induced strong neutralizing antibody responses and protected hamsters against SARS-CoV-2 disease at doses of just 0.5-5 ng of spike protein, without adjuvant, demonstrating that antigen-display exosomes are particularly immunogenic, with important implications for both structural and expression-dependent vaccines.

bioengineering↗

bioRxiv2024

Integrated Analyses of Multi-omic Data Derived from Paired Primary Lung Cancer and Brain Metastasis Reveals the Metabolic Vulnerability as a Novel Therapeutic Target

Lung cancer brain metastases (LC-BrMs) are frequently associated with dismal mortality rates in patients with lung cancer; however, standard of care therapies for LC-BrMs are still limited in their efficacy. A deep understanding of molecular mechanisms and tumor microenvironment of LC-BrMs will provide us with new insights into developing novel therapeutics for treating patients with LC-BrMs. Here, we performed integrated analyses of genomic, transcriptomic, proteomic and metabolomic data which were derived from a total number of 174 patients with paired and unpaired primary lung cancer and LC-BrM, spanning four published and two newly generated patient cohorts on both bulk and single cell levels. We uncovered that LC-BrMs exhibited significantly higher intra-tumor heterogeneity. We also observed that mutations in a subset of genes were almost always shared by both primary lung cancers and LC-BrM lesions, including TTN, TP53, MUC16, LRP1B, RYR2, and EGFR. In addition, the genome-wide landscape of somatic copy number alterations was similar between primary lung cancers and LC-BrM lesions. Nevertheless, several regions of focal amplification were significantly enriched in LC-BrMs, including 5p15.33 and 20q13.33. Intriguingly, integrated analyses of transcriptomic, proteomic and metabolomic data revealed mitochondrial-specific metabolism was activated but tumor immune microenvironment was suppressed in LC-BrMs. Subsequently, we validated our results by conducting real-time quantitative reverse transcription PCR experiments, immunohistochemistry and multiplexed immunofluorescence staining of patients paired tumor specimens. Patients with a higher expression of mitochondrial metabolism genes but a lower expression of immune genes in their LC-BrM lesions tended to have a worse survival outcome. Therapeutically, targeting oxidative phosphorylation with gamitrinib in patient-derived organoids specific to LC-BrMs induced apoptosis and inhibited cell proliferation. The combination of gamitrinib plus anti-PD-1 immunotherapy significantly improved survival of mice bearing LC-BrMs. In conclusion, our findings not only provide comprehensive and integrated perspectives of molecular underpinnings of LC-BrMs but also contribute to the development of a potential, rationale-based combinatorial therapeutic strategy with the goal of translating it into clinical trials for patients with LC-BrMs.

cancer biology↗

bioRxiv2023

Principles of visual cortex excitatory microcircuit organization

Microcircuit function is determined by patterns of connectivity and short-term plasticity that vary with synapse type. Elucidating microcircuit function therefore requires synapse-specific investigation. The state of the art for synapse-specific measurements has long been paired recordings. Although powerful, this method is slow, leading to a throughput problem. To improve yield, we therefore created optomapping -- an approximately 100-fold faster 2-photon optogenetic method -- which we validated with paired-recording data. Using optomapping, we tested 15,433 candidate excitatory inputs to find 1,184 connections onto pyramidal, basket, and Martinotti cells in mouse primary visual cortex, V1. We measured connectivity, synaptic weight, and short-term dynamics across the V1 layers. We found log-normal synaptic strength distributions, even in individual inhibitory cells, which was previously not known. We reproduced the canonical circuit for pyramidal cells but found surprising and differential microcircuit structures, with excitation of basket cells concentrated to layer 5, and excitation of Martinotti cells dominating in layer 2/3. Excitation of inhibitory cells was denser, stronger, and farther-reaching than excitation of excitatory cells, which promotes stability and difference-of-Gaussian connectivity. We gathered an excitatory short-term plasticitome, which revealed that short-term plasticity is simultaneously target-cell specific and dependent on presynaptic cortical layer. Peak depolarization latency in pyramidal cells also emerged as more heterogeneous, suggesting heightened sensitivity to redistribution of synaptic efficacy. Optomapping additionally revealed high-order connectivity patterns including shared-input surplus for interconnected pyramidal cells in layer 6. Optomapping thus offered both resolution to the throughput problem and novel insights into the principles of neocortical excitatory fine structure. HIGHLIGHTSO_LI2-photon optomapping of microcircuits is verified as fast, accurate, and reliable C_LIO_LISynaptic weights distribute log-normally even for individual inhibitory neurons C_LIO_LIMaximal excitation of basket and Martinotti cells in layer 5 and 2/3, respectively C_LIO_LIShort-term plasticity depends on layer in addition to target cell C_LI

neuroscience↗

bioRxiv2023

Predicting biomarker for the acute pulmonary embolism by using gene ontology and machine learning

Key PointsEarly and Accurate Diagnosis Essential: Acute pulmonary embolism (PE) is a critical condition that demands prompt and precise diagnosis for effective treatment. Limitations of Current Diagnostics: Existing diagnostic methods like Computed Tomography Pulmonary Angiography (CTPA) have certain limitations, leading to the exploration of alternative approaches. Potential of Blood-Based Biomarkers: A recent study focused on identifying blood-based biomarkers for PE. This involved using gene ontology analysis and machine learning methods to analyze gene expression data from both PE patients and healthy controls. Gene Selection and Analysis: The study selected 20 genes for detailed analysis. These included various coagulation factors, fibrinolytic genes, and inflammation markers. Gene Ontology enrichment analysis was performed to understand the biological processes and molecular functions of these genes. Machine Learning for Diagnosis: Supervised machine learning algorithms were utilized to create classification models using the expression levels of these 20 genes. The models demonstrated promising results in distinguishing PE patients from healthy individuals. Acute pulmonary embolism (PE) is a life-threatening condition requiring early and accurate diagnosis. Current diagnostic methods like CTPA have limitations, and a study aimed to identify potential blood-based biomarkers for PE using gene ontology analysis and machine learning methods. Gene expression data of PE patients and healthy controls were obtained from the Gene Expression Omnibus database. A total of 20 genes were selected for further analysis, including coagulation factors F7, F10, F12, fibrinolytic genes PLAT, SERPINE1 and SERPINE2, and inflammation markers SELE, VCAM1 and ICAM. Gene Ontology enrichment analysis was performed to identify biological processes and molecular functions overrepresented among the candidate genes. Supervised machine learning algorithms were applied to build classification models using the expression levels of the 20 genes as features. Nested cross-validation was employed to assess model performance. The RF model achieved the highest area under the receiver operating characteristic curve of 0.89, indicating excellent discrimination between PE patients and controls based on the gene expression signature. Validation in larger cohorts is warranted to clinically translate these findings into a non-invasive diagnostic test for PE.

genomics↗