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PubMed2006

Vascular biology: cellular and molecular profiling.

Our understanding of the mechanisms underlying cerebrovascular atherosclerosis has improved in recent years, but significant gaps remain. New insights into the vascular biological processes that result in ischemic stroke may come from cellular and molecular profiling studies of the peripheral blood. In recent cellular profiling studies, increased levels of a proinflammatory T-cell subset (CD4 (+)CD28 (-)) have been associated with stroke recurrence and death. Expansion of this T-cell subset may occur after ischemic stroke and be a pathogenic mechanism leading to recurrent stroke and death. Increases in certain phenotypes of endothelial cell microparticles have been found in stroke patients relative to controls, possibly indicating a state of increased vascular risk. Molecular profiling approaches include gene expression profiling and proteomic methods that permit large-scale analyses of the transcriptome and the proteome, respectively. Ultimately panels of genes and proteins may be identified that are predictive of stroke risk. Cellular and molecular profiling studies of the peripheral blood and of atherosclerotic plaques may also pave the way for the development of therapeutic agents for primary and secondary stroke prevention.

Atherosclerosis↗

PubMed2000

Operomics: molecular analysis of tissues from DNA to RNA to protein.

The identification of coding sequences in a number of species, including human in the near future, has ushered in the post-genome era. In this era, technologies are becoming available that allow the profiling of tissues and cell populations at the genomic, transcriptomic and proteomic levels. The molecular analysis of tissues at all three levels has been referred to as operomics. This review covers some basic technologies for operomics and their application to some lymphoid disorders. It is proposed that no one type of analysis is fully informative and that information that can be derived from the different compartments encompassed in operomics is complementary. Prospects for introducing such profiling technologies into the clinical laboratory will depend on their robustness, their user friendliness and the clinical relevance of the added information they provide, which cannot be captured through other technologies in use in the clinical laboratory.

Genomics↗

PubMed2004

Clinical impact of gene expression profiling on oncology diagnosis, prognosis, and treatment.

Genomics has enabled the examination of the totality of disease at the transcriptome level. Dependent upon a myriad of genetic aberrations for its pathogenesis, cancer has been the focus of gene expression profiling studies that have highlighted the potential clinical applications of this technology. This type of molecular profiling has the potential to enhance the ability of pathologists and oncologists to correctly classify tumors, not just into existing subgroups which may or may not have clear prognostic implications, but into new groups which carry predictable correlations with outcomes. Ultimately, these outcome predictions can be tied to specific treatment regimens, allowing clinicians to predict at the time of diagnosis to which therapy a given patient may best respond. Although this ultimate goal of personalized therapy remains in the future, the numerous studies to date have clearly demonstrated the overall feasibility of this approach. This review will showcase a few of these studies in several key tumor types with the goal of demonstrating which type of studies have been conducted and what types of results are currently possible.

Breast Neoplasms↗

PubMed2025

Identification of Novel Wraparound Transcripts in JC Polyomavirus.

JC polyomavirus (JCPyV) is a ubiquitous pathogen that causes progressive multifocal leukoencephalopathy (PML). Although a recent study using next-generation sequencing (NGS) provided detailed transcriptome atlases for polyomaviruses (PyVs) such as BK polyomavirus and simian virus 40, the transcriptome of JCPyV remains poorly characterized. Here, we conducted a comprehensive analysis using both short-read and long-read NGS technologies to construct a transcriptome atlas of JCPyV. RNA extracted from IMR-32 and HEK293 cells transfected with the circular JCPyV genome was analyzed, leading to the identification of 39 previously uncharacterized viral transcripts in addition to 12 known ones. Among the novel transcripts, we identified wraparound transcripts, conserved across PyVs, which are generated through continuous, multicyclic transcription of the circular viral genome. These included both late transcripts containing leader-to-leader repeated sequences and SuperT transcripts with multiple LxCxE motifs. Notably, wraparound transcripts, including SuperT transcripts, were also detected in brain tissues from PML patients. Collectively, this study significantly expands our understanding of the JCPyV transcriptome, revealing the expression of wraparound transcripts in PML lesions. These findings provide valuable insights into the molecular basis of JCPyV gene expression and PML pathogenesis, potentially facilitating the development of effective countermeasures against PML.

JC Virus↗

PubMed2005

Isogene specific oligo arrays reveal multifaceted changes in gene expression during grape berry (Vitis vinifera L.) development.

The transition from a green, hard, and acidic pericarp to a sweet, soft, coloured, and sugar-rich ripe fruit occurs in many unrelated fruit species. High throughput identification of differentially expressed genes in grape berry has been achieved by the use of 50-mers oligoarrays bearing a set of 3,200 Unigenes from Vitis vinifera to compare berry transcriptome at nine developmental stages. Analysis of transcript profiles revealed that most activations were triggered simultaneously with softening, occurring within only 24 h for an individual berry, just before any change in colouration or water, sugar, and acid content can be detected. Although most dramatically induced genes belong to unknown functional categories, numerous changes occur in the expression of isogenes involved in primary and secondary metabolism during ripening. Focusing on isogenes potentially significant in development regulation (hormonal control of transcription factor) revealed a possible role for several hormones (cytokinin, gibberellin, or jasmonic acid). Transcription factor analysis revealed the induction of RAP2 and WRKY genes at véraison, suggesting increasing biotic and abiotic stress conditions during ripening. This observation was strengthened by an increased expression of multiple transcripts involved in sugar metabolism and also described as induced in other plant organs during stress conditions. This approach permitted the identification of new isogenes as possible control points: a glutathione S-transferase exhibits the same expression profile as anthocyanin accumulation and a new putative sugar transporter is induced in parallel with sugar import.

Anthocyanins↗

PubMed2025

Parabacteroides goldsteinii mitigates parkinsonism in LRRK2 mutant mice by reducing neuroinflammation through Gut-Brain axis.

INTRODUCTION: Alterations in the gut microbiota accompanied by intestinal inflammation are early features of Parkinson's disease (PD). Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene represent a common genetic risk factor for PD and inflammatory bowel disease. Parabacteroides goldsteinii has been reported to alleviate intestinal and systemic inflammation. However, whether modulation of the gut microenvironment at early disease stage can attenuate PD progression remains unclear. OBJECTIVE: To investigate the impact of P. goldsteinii colonization prior to the onset of motor dysfunction on PD progression. METHODS: We established a germ-free PD mouse model carrying the LRRK2 G2019S mutation and administered P. goldsteinii orally at the pre-symptomatic stage to evaluate its effects on motor performance and PD-related neuropathology. Spatial and bulk RNA transcriptomic analyses of brain tissue, together with cytokine profiling, were conducted to assess central changes. To investigate gut immunomodulatory mechanisms, we performed intestinal bulk and single-cell RNA sequencing, spectral flow cytometry as well as cellular bioenergetic analyses. RESULTS: Germ-free conditions partially alleviated PD-like phenotypes in LRRK2 G2019S mice. Colonization with P. goldsteinii at 5-months of age, prior to motor symptom onset, further improved locomotor performance, reduced neuronal α-synuclein aggregations, and mitigated microglial activation and dopaminergic neurodegeneration. Neuroprotection was mediated through enhanced noncanonical neuronal IL-12 receptor-dependent neurotrophic support without activating the canonical STAT4 phosphorylation pathway, along with suppression of microglial activation and downregulation of LRRK2 kinase activity. At the intestinal level, P. goldsteinii suppressed TLR4-driven inflammation, expanded anti-inflammatory intraepithelial CD4+CD8αα+ T cells, promoted dendritic cell and macrophage differentiation, upregulated epithelial tight-junction genes, and improved mitochondrial bioenergetics in intestinal cells. CONCLUSION: P. goldsteinii colonization attenuates the progression of LRRK2-associated parkinsonism by restoring intestinal homeostasis and reducing neuroinflammation. These findings underscore the therapeutic potential of modulating the gut-immune-brain axis during the prodromal stage of PD.

Animals↗

PubMed2024

Organ-delimited gene regulatory networks provide high accuracy in candidate transcription factor selection across diverse processes.

Organ-specific gene expression datasets that include hundreds to thousands of experiments allow the reconstruction of organ-level gene regulatory networks (GRNs). However, creating such datasets is greatly hampered by the requirements of extensive and tedious manual curation. Here, we trained a supervised classification model that can accurately classify the organ-of-origin for a plant transcriptome. This K-Nearest Neighbor-based multiclass classifier was used to create organ-specific gene expression datasets for the leaf, root, shoot, flower, and seed in Arabidopsis thaliana. A GRN inference approach was used to determine the: i. influential transcription factors (TFs) in each organ and, ii. most influential TFs for specific biological processes in that organ. These genome-wide, organ-delimited GRNs (OD-GRNs), recalled many known regulators of organ development and processes operating in those organs. Importantly, many previously unknown TF regulators were uncovered as potential regulators of these processes. As a proof-of-concept, we focused on experimentally validating the predicted TF regulators of lipid biosynthesis in seeds, an important food and biofuel trait. Of the top 20 predicted TFs, eight are known regulators of seed oil content, e.g., WRI1, LEC1, FUS3. Importantly, we validated our prediction of MybS2, TGA4, SPL12, AGL18, and DiV2 as regulators of seed lipid biosynthesis. We elucidated the molecular mechanism of MybS2 and show that it induces purple acid phosphatase family genes and lipid synthesis genes to enhance seed lipid content. This general approach has the potential to be extended to any species with sufficiently large gene expression datasets to find unique regulators of any trait-of-interest.

Arabidopsis↗

PubMed2026

The multilayered cuticle underlying structural coloration in red algae shares features with the metazoan extracellular matrix.

Structural coloration, a physical phenomenon observed in many living organisms, may arise from the interference of light with highly organized surface nanostructures. In some seaweeds, these nanostructures consist of cuticular lamellae in the outer part of the extracellular matrix (ECM) of the epidermis. However, the chemical composition of seaweed cuticles is poorly understood and the molecular components of lamellae remain unidentified. Here, we use integrated genomic, transcriptomic, proteomic, and metabolomic approaches together with analytical profiling of carbohydrates to determine the composition of the multilayered cuticle in the red alga Chondrus crispus and assess its evolutionary conservation. The structural assembly reveals common features with the ECM of animals. The carbohydrate fraction includes a complex mixture of carrageenans and glycosaminoglycan-like compositions. A major von Willebrand factor A domain protein, Lamellae Cohesive Protein, plays a critical role in protein-protein interactions and binding to sulfated polysaccharides. We have further identified the major proteins of the algal cuticle, providing a framework for addressing the evolutionary origins of the cuticle and raising important questions regarding its role, particularly across the red algal life cycle marked by major structural differences in its ECM.

Extracellular Matrix↗

PubMed2005

Suppression of death receptor-mediated apoptosis by 1,25-dihydroxyvitamin D3 revealed by microarray analysis.

Recent studies suggest that growth inhibition by 1,25-dihydroxyvitamin D3 represents an innovative approach to ovarian cancer therapy. To understand the molecular mechanism of 1,25-dihydroxyvitamin D3 action, we profiled the hormone-induced changes in the transcriptome of ovarian cancer cells using microarray technology. More than 200 genes were identified to be regulated by 1,25-dihydroxyvitamin D3. Reverse transcription-PCR analyses confirmed the regulation of a group of apoptosis-related genes, including the up-regulation of the decoy receptor that inhibits tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) action, TRAIL receptor 4, and the down-regulation of Fas, the receptor that mediates the action of Fas ligand. The regulation was further confirmed at the protein level. Consistent with the regulation of the death receptors, pretreatment with 1,25-dihydroxyvitamin D3 decreased apoptosis induced by TRAIL and Fas ligand. Because persistent 1,25-dihydroxyvitamin D3 treatment has been shown to induce apoptosis in ovarian cancer, the hormone appears to exert a dual effect on the death of ovarian cancer cells. Knockdown of TRAIL receptor 4 by RNA interference or ectopic expression of Fas relieved the suppressive effect of 1,25-dihydroxyvitamin D3, showing that molecular manipulation of death receptors is a viable approach to overcome the protective effect of 1,25-dihydroxyvitamin D3 on the apoptosis of ovarian cancer. These strategies may allow ovarian cancer patients to benefit from therapy with both 1,25-dihydroxyvitamin D3 and ligands for death receptors, such as TRAIL, shown to selectively induce apoptosis in cancer but not normal cells.

Apoptosis↗

PubMed2026

Perineuronal net degradation in aggressive glioblastomas with KANK1::NTRK2 fusions.

BACKGROUND: Approximately 10% of glioblastomas harbor targetable genomic fusions. NTRK2 participates in a variety of fusion events that drive tumorigenesis. Two previous reports have described KANK1::NTRK2 fusions in adult glioblastoma patients with poor survival. METHODS: We performed a retrospective analysis of glioblastoma patients treated at Dartmouth-Hitchcock Medical Center (DHMC) from 2020 to 2025 to identify cases harboring KANK1::NTRK2 fusions. Clinical presentation, treatment, histopathologic features, and outcomes were reviewed. In addition, we conducted GeoMx whole-transcriptome and high-plex proteomic digital spatial profiling of a KANK1::NTRK2-positive glioblastoma and a comparator tumor from a long-term survivor. Candidate biomarkers were orthogonally validated using immunohistochemistry and/or immunofluorescence. RESULTS: Two patients with KANK1::NTRK2 fusion glioblastoma were identified, both demonstrating rapid progression, therapeutic resistance, and survival of less than 7 months. Proteomic profiling showed increased expression and activation of canonical NTRK2 downstream signaling pathways, particularly MEK1/2 and ERK1/2. This was accompanied by upregulation of extracellular matrix remodeling enzymes, including MMP3, MMP14, and ADAM15, along with reduced expression of extracellular matrix-associated transcripts and perineuronal net components in particular compared to a non-fusion glioblastoma. CONCLUSIONS: These limited, hypothesis-generating findings suggest constitutive NTRK2 signaling may promote coordinated extracellular matrix degradation and remodeling, potentially facilitating rapid and aggressive tumor growth and invasion in a subset of glioblastomas.

NTRK gene fusion↗

PubMed2025

Exploring Potential Causality and Molecular Mechanisms between Heart Failure and Renal Failure: Insights from Mendelian Randomization Studies, the MIMIC-IV Database and the Gene Expression Omnibus Database.

UNLABELLED: Introduction: Heart failure (HF) and renal failure (RF) frequently coexist as cardiorenal syndrome, but their underlying causal mechanisms remain poorly defined. METHODS: This study applied Mendelian randomization (MR) using genome-wide association study (GWAS) datasets to investigate the causal effect of HF on RF. The inverse variance weighted method assessed causality, and summary-data-based MR (SMR) was used to identify therapeutic targets. Additional analyses included 211 gut microbiota traits and 1,400 serum metabolites. Validation was performed using the MIMIC-IV database. Transcriptomic data were analyzed to identify differentially expressed genes (DEGs) and key transcription factors (TFs). RESULTS: This study found that HF significantly increases the risk of RF (OR = 1.54, 95% CI: 1.07-2.23, p = 0.020). SMR analysis identified SURF1 and MAP3K11 as potential therapeutic targets for HF and RF. One gut microbiota genus and one serum metabolite showed causal associations with both diseases. MIMIC-IV data supported the HF-RF association (OR = 2.94, 95% CI: 2.81-3.07, p < 0.001). A total of 11 overlapping DEGs were enriched in the MAPK cascade, with RELA identified as a key TF. CONCLUSION: This study provides genetic and molecular evidence supporting a causal role of HF in RF, highlighting microbial, metabolic, and immune mechanisms as potential therapeutic targets. .

Humans↗

PubMed2025

Methylation patterns of the nasal epigenome of hospitalized SARS-CoV-2 positive patients reveal insights into molecular mechanisms of COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has varied presentations from asymptomatic to death. Efforts to identify factors responsible for differential COVID-19 severity include but are not limited to genome wide association studies (GWAS) and transcriptomic analysis. More recently, variability in host epigenomic profiles have garnered attention, providing links to disease severity. However, whole epigenome analysis of the respiratory tract, the target tissue of SARS-CoV-2, remains ill-defined. RESULTS: We interrogated the nasal methylome to identify pathophysiologic drivers in COVID-19 severity through whole genome bisulfite sequencing (WGBS) of nasal samples from COVID-19 positive individuals with severe and mild presentation of disease. We noted differential DNA methylation in intergenic regions and low methylated regions (LMRs), demonstrating the importance of distal regulatory elements in gene regulation in COVID-19 illness. Additionally, we demonstrated differential methylation of pathways implicated in immune cell recruitment and function, and the inflammatory response. We found significant hypermethylation of the FUT4 promoter implicating impaired neutrophil adhesion in severe disease. We also identified hypermethylation of ELF5 binding sites suggesting downregulation of ELF5 targets in the nasal cavity as a factor in COVID-19 phenotypic variability. CONCLUSIONS: This study demonstrated DNA methylation as a marker of the immune response to SARS-CoV-2 infection, with enhancer-like elements playing significant roles. It is difficult to discern whether this differential methylation is a predisposing factor to severe COVID-19, or if methylation differences occur in response to disease severity. These differences in the nasal methylome may contribute to disease severity, or conversely, the nasal immune system may respond to severe infection through differential immune cell recruitment and immune function, and through differential regulation of the inflammatory response.

Humans↗

PubMed2026

Transcriptome-based epigenetic screening identifies DNA hypermethylation signatures as prognostic biomarkers in oral squamous cell carcinoma.

Promoter DNA hypermethylation is a key epigenetic mechanism of gene silencing in cancer, yet the DNA hypermethylome of oral squamous cell carcinoma (OSCC) and its prognostic relevance remain poorly characterized. Here, we systematically identified and validated novel hypermethylated genes with prognostic significance in OSCC using a genome-wide discovery and multi-platform validation strategy. Candidate genes were first identified by pharmacologic demethylation combined with RNA sequencing across OSCC cell lines, then validated by quantitative RT-PCR, methylation-specific PCR, and bisulfite sequencing in OSCC cell lines, normal oral mucosa, and primary OSCC tumors, with independent confirmation in the TCGA-HNSC dataset. Immunohistochemistry confirmed protein-level silencing, and Kaplan-Meier survival analysis assessed prognostic significance across both cohorts. This pipeline identified five candidate genes, GPX3, ANG, CTGF, GPRC5B, and BAMBI, exhibiting cancer-specific promoter hypermethylation associated with transcriptional and protein silencing in OSCC. Validation in oral cavity tumor samples extracted from the TCGA-HNSC dataset confirmed tumor-specific hypermethylation and revealed significant inverse correlations between methylation and expression for GPX3, GPRC5B, and CTGF. Notably, CTGF hypermethylation was independently associated with poor overall survival in both cohorts (institutional cohort, p=0.03; oral tumor subset from TCGA-HNSC, p=0.01), and a combined ANG+CTGF methylation signature showed superior and reproducible prognostic performance across both platforms. Pathway analysis linked these genes to epithelial-mesenchymal transition and interferon response signaling. This study establishes the first validated DNA methylation biomarker panel for OSCC prognosis, identifying CTGF hypermethylation as a robust prognostic driver with translational potential for clinical risk stratification.

Humans↗

PubMed2026

transFusion: a novel comprehensive platform for integration analysis of single-cell and spatial transcriptomics.

MOTIVATION: Understanding spatial organization, intercellular interactions, and regulatory networks within the spatial context of tissues is crucial for uncovering complex biological processes and disease mechanisms. Spatial transcriptomics technologies have revolutionized this field by enabling the spatially resolved profiling of gene expression. 10× Visium has emerged as the predominant spatial technology, but its low resolution and the complexity of integrating multimodal datasets present significant analytical challenges, particularly for researchers with limited computational and statistical expertise. Current spatial transcriptomics analysis platforms generally fall short of effectively integrating multimodal data and maximizing the utility of spatial information-such as uncovering complex cellular spatial dependencies, multimodal gradient patterns, and spatial coexpression of ligand-receptor pairs and regulatory networks related to disease or biological states-thereby limiting their ability to provide comprehensive end-to-end analytical workflows when analyzing 10× Visium data. RESULTS: To address these limitations, we developed transFusion, a novel, advanced web-based platform specializing in the most comprehensive and effective integration analysis of scRNA-seq and 10× Visium spatial transcriptomics data. transFusion offers 12 key functions, from basic visualization to advanced analyses, including intercellular dependency analysis, ligand-receptor coexpression identification and visualization, and spatial multimodal gradient variation patterns. Two case studies were used to demonstrate transFusion's capabilities in exploring tissue architecture, intercellular communication, dependency networks, and multimodal gradient variation patterns with minimal computational skills and statistical expertise. transFusion provides a flexible and powerful framework for multimodal data integration analysis. AVAILABILITY AND IMPLEMENTATION: transFusion is freely available at https://github.com/WQLin8/transFusion.

Spatial Transcriptomics↗

PubMed2002

The dynamics of the Saccharomyces carlsbergensis brewing yeast transcriptome during a production-scale lager beer fermentation.

The transcriptome of a lager brewing yeast (Saccharomyces carlsbergensis, syn. of S. pastorianus), was analysed at 12 different time points spanning a production-scale lager beer fermentation. Generally, the average expression rapidly increased and had a maximum value on day 2, then decreased as the sugar got consumed. Especially genes involved in protein and lipid biosynthesis or glycolysis were highly expressed during the beginning of the fermentation. Similarities as well as significant differences in expression profiles could be observed when comparing to a previous transcriptome analysis of a laboratory yeast grown in YPD. The regional distribution of various expression levels on the chromosomes appeared to be random or near-random and no reduction in expression near telomeres was observed.

Beer↗

PubMed2002

A partial transcriptome of human epidermis.

Serial analysis of gene expression (SAGE) is a powerful technique for global expression profiling without prior knowledge of the genes of interest. We carried out SAGE analysis of purified keratinocytes derived from human skin biopsy specimens, resulting in a partial transcriptome of human epidermis. We identified 7645 unique SAGE tags with quantitative information from 15,131 collected SAGE tags obtained from approximately 3 x 10(6) epidermal cells. This catalog contains a large number of genes that were not previously known to be expressed by human epidermis. Comparison with the databases of all known human SAGE tags allowed us to identify a number of keratinocyte-specific tags that putatively correspond to formerly unknown genes. Surprisingly, human epidermal keratinocytes in vivo show relatively low expression levels of genes typically associated with epidermal differentiation, whereas the expression levels of housekeeping genes are considerably higher than in cultured keratinocytes. This study provides a first step toward a transcriptome of human epidermis and, as such, harbors a wealth of information to identify genes involved in skin function, and candidate genes for genetic skin disorders.

Base Sequence↗

PubMed2007

Integrative profiling of metabolites and proteins: improving pattern recognition and biomarker selection for systems level approaches.

Methods such as mRNA expression profiling have provided a vast amount of genomic and transcriptomic information about plants and other organisms. However, there is explicit indication that considerable metabolic control is executed on the metabolite and on the protein level including protein modifications, thereby constituting the phenotypic plasticity. Consequently, the analysis of the molecular phenotype demands the step toward mass spectrometry (MS)-based postgenomic techniques such as metabolomics and proteomics. This chapter describes a straightforward protocol for simultaneously extracting metabolites and proteins from the same biological sample in preparation for MS analysis. Furthermore, protocols for profiling polar metabolites using gas chromatography time-of-flight MS and for shotgun proteomics using liquid chromatography-MS are discussed. A practical course is laid out that outlines all the basic steps, from harvesting to data analysis. These steps enable the correlative study of metabolite and protein dynamics with minimal technical variation. Biological variability of independent samples is exploited for variance analysis and pattern recognition.

Arabidopsis↗

PubMed2026

Integrating histology and spatial transcriptomics via multimodal transformers and contrastive representation learning for accurate gene expression prediction.

Predicting spatial gene expression from Histological images is a fundamental task in understanding tissue organization and molecular phenotypes. However, existing methods often rely on single-model representations or lack effective alignment between image and transcriptomic features. To address these limitations, we propose a unified multimodal learning framework that integrates histological imaging and spatial transcriptomics through a shared latent representation space. Specifically, histological H&E images are encoded by a ResNet50-based convolutional stem and a MobileViT Transformer backbone to extract hierarchical visual representations. Both modalities are projected into a shared latent space via linear-GELU-dropout transformation blocks, enabling cross-modal alignment through a contrastive learning objective that maximizes agreement between the corresponding image and the spot embeddings. Experimental results on the 10x Genomics Visium dataset of human liver tissue demonstrate that MViTGene achieves significantly higher prediction accuracy than existing methods across multiple gene subsets, with improvements of 20%, 33%, and 12% in predicting marker genes, highly expressed genes, and highly variable genes, respectively. The significant improvement in relevance indicates that the model can more accurately capture the true correspondence between tissue morphology and gene expression, therefore enabling more reliable biological interpretation. It provides a computational tool for high-throughput spatial gene expression prediction that balances performance and interpretability.

Humans↗