Biology subjects

Zeng, X.

Publications and source records attributed to Zeng, X..

At least 109 records · Page 6Linked to original sources

bioRxiv2024

Mpox virus (MPXV) vertical transmission and fetal demise in a pregnant rhesus macaque model

Infection with clade I Mpox virus (MPXV) results in adverse pregnancy outcomes, yet the potential for vertical transmission resulting in fetal harm with clade IIb MPXV, the clade that is currently circulating in the Western Hemisphere, remains unknown. We established a rhesus macaque model of vertical MPXV transmission with early gestation inoculation. Three pregnant rhesus macaques were inoculated intradermally with 1.5 x 10^5 plaque forming units (PFU) of clade IIb MPXV near gestational day (GD) 30 and animals were monitored for viremia and maternal and fetal well-being. Animals were euthanized to collect tissues at 5, 14, or 25 days post-inoculation (dpi). Tissues were evaluated for viral DNA (vDNA) loads, infectious virus titers, histopathology, MPXV mRNA and protein localization, as well as MPXV protein co-localization with placental cells including, Hofbauer cells, mesenchymal stromal cells, endothelial cells, and trophoblasts. vDNA was detected in maternal blood and skin lesions by 5 dpi. Lack of fetal heartbeat was observed at 14 or 25 dpi for two dams indicating fetal demise; the third dam developed significant vaginal bleeding at 5 dpi and was deemed an impending miscarriage. vDNA was detected in placental and fetal tissue in both fetal demise cases. MPXV localized to placental villi by ISH and IHC. Clade IIb MPXV infection in pregnant rhesus macaques results in vertical transmission to the fetus and adverse pregnancy outcomes, like clade I MPXV. Further studies are needed to determine whether antiviral therapy with tecovirimat will prevent vertical transmission and improve pregnancy outcomes. One Sentence SummaryClade IIb Mpox virus infection of pregnant rhesus macaques results in vertical transmission from mother to fetus and adverse pregnancy outcomes.

pathology↗

bioRxiv2024

Spatiotemporally resolved transcriptome atlas of developing mouse placenta reveals mechanisms of embryonic lethality.

Proper placentation is fundamental to the growth and viability of the maturing embryo. However, a thorough grasp of the spatial organization of cell types, their interactions, and gene expression patterns along the maternal-fetal function during placental development remains incomplete. Here, we utilized Stereo-seq to construct the spatiotemporal transcriptomic atlas of the mouse placenta (STAMP) spanning embryonic (E) days 9.5 to 18.5 at single cell resolution (https://db.cngb.org/stomics/stamp/). This resource delineates spatially resolved cellular dynamics and gene expression patterns across placental and maternal compartments. We identified distinct glycogen trophoblast cell (GC) subclusters, mapped their developmental trajectories, and uncovered transcriptional transitions accompanying their migration from the junctional zone to the maternal decidua from E12.5 onward. In a defective placentation model with perinatal lethality, GCs abnormally persisted at E18.5 with excessive glycogen and reduced degradation metabolites in placenta and fetal liver, indicating impaired glycogen breakdown. Maternal glucose supplementation restored glucose levels and rescued fetal survival, underscoring GC-mediated metabolic support as critical for viability. Together, this study provides a comprehensive spatiotemporal placental atlas and demonstrates that GC-mediated glycogen metabolism is essential for sustaining fetal viability.

developmental biology↗

bioRxiv2024

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimers disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

genomics↗

bioRxiv2024

Gene2role: a role-based gene embedding method for comparative analysis of signed gene regulatory networks

MotivationUnderstanding the dynamics of gene regulatory networks (GRNs) across various cellular states is crucial for deciphering the underlying mechanisms governing cell behavior and functionality. However, current comparative analytical methods, which often focus on simple topological information such as the degree of genes, are limited in their ability to fully capture the similarities and differences among the complex GRNs. ResultsWe present Gene2role, a gene embedding approach that leverages multi-hop topological information from genes within signed GRNs. Initially, we demonstrated the effectiveness of Gene2role in capturing the intricate topological nuances of genes using GRNs inferred from four distinct data sources. Then, applying Gene2role to integrated GRNs allowed us to identify genes with significant topological changes across cell types or states, offering a fresh perspective beyond traditional differential gene expression analysis. Additionally, we quantified the stability of gene modules between two cellular states by measuring the changes in the gene embeddings within these modules. In conclusion, our method augments the existing toolkit for probing the dynamic regulatory landscape, thereby opening new avenues for understanding gene behavior and interaction patterns across cellular transitions.

bioinformatics↗

bioRxiv2024

Repeat and haplotype aware error correction in nanopore sequencing reads with DeChat

Error self-correction is a pivotal first step in the analysis of long-read sequencing data. However, most existing methods for this purpose are primarily tailored for noisy sequencing data with error rates exceeding 5%, often collapsing true variants in repeats and haplotypes. Alternatively, some methods are heavily optimized for PacBio HiFi reads, leaving a gap in methods specifically designed for Nanopore R10 reads basecalled with high accuracy or super accuracy models, which typically have error rates below 2%. Here, we introduce DeChat, a novel approach specifically designed for Nanopore R10 reads. DeChat enables repeat- and haplotype-aware error correction, leveraging the strengths of both de Bruijn graphs and variant-aware multiple sequence alignment to create a synergistic approach. This approach avoids read overcorrection, ensuring that variants in repeats and haplotypes are preserved while sequencing errors are accurately corrected. Benchmarking experiments reveal that reads corrected using DeChat exhibit substantially fewer errors, ranging from several times to two orders of magnitude lower, compared to the current state-of-the-art approaches. Furthermore, the application of DeChat for error correction significantly improves genome assembly across various aspects. DeChat is implemented as a highly efficient, standalone, and user-friendly software and is publicly available at https://github.com/LuoGroup2023/DeChat.

bioinformatics↗

bioRxiv2024

Structural basis for the inhibition of coronaviral main proteases by PF-00835231

The main protease (Mpro) of coronaviruses plays a key role in viral replication, thus serving as a hot target for drug design. It has been proven that PF-00835231 is promising inhibitor of SARS-CoV-2 Mpro. Here, we report the inhibition potency of PF-00835231 against SARS-CoV-2 Mpro and seven Mpro mutants (G15S, M49I, Y54C, K90R, P132H, S46F, and V186F) from SARS-CoV-2 variants. The results confirm that PF-00835231 has broad-spectrum inhibition against various coronaviral Mpros. In addition, the crystal structures of SARS-CoV-2 Mpro, SARS-CoV Mpro, MERS-CoV Mpro, and seven SARS-CoV-2 Mpro mutants (G15S, M49I, Y54C, K90R, P132H, S46F, and V186F) in complex with PF-00835231 are solved. A detailed analysis of these structures reveal key determinants essential for inhibition and elucidates the binding modes of different coronaviral Mpros. Given the importance of the main protease for the treatment of coronaviral infection, structural insights into the Mpro inhibition by PF-00835231 can accelerate the design of novel antivirals with broad-spectrum efficacy against different human coronaviruses.

molecular biology↗

bioRxiv2024

Regional Glymphatic Dysfunction is linked to Spinocerebellar Ataxia Type 3 pathophysiology

Spinocerebellar ataxia type 3 (SCA3) involves neuroinflammation and imbalance between production and clearance of proteins which affects the glymphatic system, the lymphatic-like, fluid-transport system in the brain. However, it is unclear whether SCA3 is related to impairments in glymphatic function. Using multimodal imaging data, 34 SCA3 patients and 36 age-, sex- and educational matched healthy controls (HCs) were compared using multiple glymphatic measurements, including choroid plexus (CP) and cerebrospinal fluid (CSF) volume, diffusion tensor imaging along the perivascular (DTI-ALPS) index, and coupling relationship between blood-oxygen-level-dependent signals and CSF flow (BOLD-CSF coupling). Then, we evaluated regional glymphatic function by dividing DTI-ALPS and BOLD-CSF coupling into anterior, middle, posterior, and cerebellum regions, thereby identifying the spatial variation of glymphatic function in the two groups. We demonstrated that compared with HCs, larger CP and CSF volumes were found in SCA3 patients. More importantly, for DTI-ALPS index and BOLD-CSF coupling, these surrogate markers for glymphatic clearance were weaker in SCA3 patients. Furthermore, altered regional glymphatic functions were most prominent in midbrain, cerebellum and middle regions. Crucially, the altered midbrain, cerebellum, middle and global glymphatic functions were accompanied by the severity of ataxia and other SCA3 symptoms. Similar to other neurodegenerative disorders, the association between multiple glymphatic indexes and SCA3 symptoms suggested that waste clearance is disrupted in SCA3 patients, which shed light on the pathogenesis of this disease from a glymphatic lens. Our findings highlighted the dysregulated glymphatic function as a novel diagnostic marker for SCA3.

neuroscience↗

bioRxiv2024

TRIP12 governs DNA Polymerase β involvement in DNA damage response and repair

The multitude of DNA lesion types, and the nuclear dynamic context in which they occur, present a challenge for genome integrity maintenance as this requires the engagement of different DNA repair pathways. Specific repair controllers that facilitate DNA repair pathway crosstalk between double strand break (DSB) repair and base excision repair (BER), and regulate BER protein trafficking at lesion sites, have yet to be identified. We find that DNA polymerase {beta} (Pol{beta}), crucial for BER, is ubiquitylated in a BER complex-dependent manner by TRIP12, an E3 ligase that partners with UBR5 and restrains DSB repair signaling. Here we find that, TRIP12, but not UBR5, controls cellular levels and chromatin loading of Pol{beta}. Required for Pol{beta} foci formation, TRIP12 regulates Pol{beta} involvement after DNA damage. Notably, excessive TRIP12-mediated shuttling of Pol{beta} affects DSB formation and radiation sensitivity, underscoring its precedence for BER. We conclude that the herein discovered trafficking function at the nexus of DNA repair signaling pathways, towards Pol{beta}-directed BER, optimizes DNA repair pathway choice at complex lesion sites. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/588474v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@70c5bdorg.highwire.dtl.DTLVardef@1c60dfborg.highwire.dtl.DTLVardef@1c00ef6org.highwire.dtl.DTLVardef@1677f2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Selective modification of ascending spinal outputs in acute and neuropathic pain states

Pain hypersensitivity arises from the plasticity of peripheral and spinal somatosensory neurons, which modifies nociceptive input to the brain and alters pain perception. We utilized chronic calcium imaging of spinal dorsal horn neurons to determine how the representation of somatosensory stimuli in the anterolateral tract, the principal pathway transmitting nociceptive signals to the brain, changes between distinct pain states. In healthy conditions, we identify stable, narrowly tuned outputs selective for cooling or warming, and a neuronal ensemble activated by intense/noxious thermal and mechanical stimuli. Induction of an acute peripheral sensitization with capsaicin selectively and transiently retunes nociceptive output neurons to encode low-intensity stimuli. In contrast, peripheral nerve injury-induced neuropathic pain results in a persistent suppression of innocuous spinal outputs coupled with activation of a normally silent population of high-threshold neurons. These results demonstrate the differential modulation of specific spinal outputs to the brain during nociceptive and neuropathic pain states.

neuroscience↗

bioRxiv2024

A PTER-dependent pathway of taurine metabolism linked to energy balance

Taurine is a conditionally essential micronutrient and one of the most abundant amino acids in humans1-3. In endogenous taurine metabolism, dedicated enzymes are involved in biosynthesis of taurine from cysteine as well as the downstream derivatization of taurine into secondary taurine metabolites4,5. One such taurine metabolite is N-acetyltaurine6. Levels of N-acetyltaurine are dynamically regulated by diverse physiologic perturbations that alter taurine and/or acetate flux, including endurance exercise7, nutritional taurine supplementation8, and alcohol consumption6,9. While taurine N-acetyltransferase activity has been previously detected in mammalian cells6,7, the molecular identity of this enzyme, and the physiologic relevance of N-acetyltaurine, have remained unknown. Here we show that the orphan body mass index-associated enzyme PTER (phosphotriesterase-related)10 is the principal mammalian taurine N-acetyltransferase/hydrolase. In vitro, recombinant PTER catalyzes bidirectional taurine N-acetylation with free acetate as well as the reverse N-acetyltaurine hydrolysis reaction. Genetic ablation of PTER in mice results in complete loss of tissue taurine N-acetyltransferase/hydrolysis activities and systemic elevation of N-acetyltaurine levels. Upon stimuli that increase taurine levels, PTER-KO mice exhibit lower body weight, reduced adiposity, and improved glucose homeostasis. These phenotypes are recapitulated by administration of N-acetyltaurine to wild-type mice. Lastly, the anorexigenic and anti-obesity effects of N-acetyltaurine require functional GFRAL receptors. Together, these data uncover enzymatic control of a previously enigmatic pathway of secondary taurine metabolism linked to energy balance.

biochemistry↗

bioRxiv2024

Dysregulated Neurofluid Coupling as a New Noninvasive Biomarker for Primary Progressive Aphasia

ObjectiveAccumulation of pathological tau is one of the primary causes of Primary Progressive Aphasia (PPA). The glymphatic system is crucial for removing metabolic waste from the brain, whereas the underlying mechanism on the interplay between impairments in glymphatic clearance and PPA is poorly understood. Therefore, the aim of this study is to investigate the role that dysregulated macroscopic cerebrospinal fluid (CSF) movement plays in the pathology of PPA. Methods56 PPA patients and 94 healthy controls (HCs) participated this work. The coupling strength between blood-oxygen-level-dependent (BOLD) signals in the gray matter and CSF flow within the subarachnoid space and ventricular system was calculated by using Pearson correlation and made comparison between the two groups. Its associations with clinical characteristics including scores from Clinical Dementia Rating (CDR), Mini-Mental State Exam, Geriatric Depression Scale and with morphological measures in the hippocampus and entorhinal cortex were also quantified. ResultsThe PPA group exhibited decreased global BOLD and CSF coupling as compared to that of HCs, indicating impaired glymphatic functions of the patients (p = 0.006). More importantly, it was discovered that BOLD-CSF coupling of PPA group rather than that of the HCs demonstrated significant correlations with the CDR scores (p = 0.04), hippocampal volume (p = 0.005), and entorhinal cortex thickness (p = 0.04). InterpretationThe measured decoupling between global brain activation (hemodynamic response) and CSF flow and its association with symptomology and brain structural changes in PPA revealed the glymphatic dysregulation in PPA. Herein, this evidence supports the potential role of BOLD-CSF coupling as a noninvasive biomarker for the detection and prediction of PPA.

neuroscience↗

bioRxiv2024

DenoiseST: A dual-channel unsupervised deep learning-based denoising method to identify spatial domains and functionally variable genes in spatial transcriptomics

Spatial transcriptomics provides a unique opportunity for understanding cellular organization and function in a spatial context. However, spatial transcriptome exists the problem of dropout noise, exposing a major challenge for accurate downstream data analysis. Here, we proposed DenoiseST, a dual-channel unsupervised adaptive deep learning-based denoising method for data imputing, clustering, and identifying functionally variable genes in spatial transcriptomics. To leverage spatial information and gene expression profiles, we proposed a dual-channel joint learning strategy with graph convolutional networks to sufficiently explore both linear and nonlinear representation embeddings in an unsupervised manner, enhancing the discriminative information learning ability from the global perspectives of data distributions. In particular, DenoiseST enables the adaptively fitting of different gene distributions to the clustered domains and employs tissue-level spatial information to accurately identify functionally variable genes with different spatial resolutions, revealing their enrichment in corresponding gene pathways. Extensive validations on a total of 18 real spatial transcriptome datasets show that DenoiseST obtains excellent performance and results on brain tissue datasets indicate it outperforms the state-of-the-art methods when handling artificial dropout noise with a remarkable margin of [~]15%, demonstrating its effectiveness and robustness. Case study results demonstrate that when applied to identify biological structural regions on human breast cancer spatial transcriptomic datasets, DenoiseST successfully detected biologically significant immune-related structural regions, which are subsequently validated through Gene Ontology (GO), cell-cell communication, and survival analysis. In conclusion, we expect that DenoiseST is a novel and efficient method for spatial transcriptome analysis, offering unique insights into spatial organization and function.

bioinformatics↗

bioRxiv2024

DUAL: deep unsupervised simultaneous simulation and denoising for cryo-electron tomography

Recent biotechnological developments in cryo-electron tomography allow direct visualization of native sub-cellular structures with unprecedented details and provide essential information on protein functions/dysfunctions. Denoising can enhance the visualization of protein structures and distributions. Automatic annotation via data simulation can ameliorate the time-consuming manual labeling of large-scale datasets. Here, we combine the two major cryo-ET tasks together in DUAL, by a specific cyclic generative adversarial network with novel noise disentanglement. This enables end-to-end unsupervised learning that requires no labeled data for training. The denoising branch outperforms existing works and substantially improves downstream particle picking accuracy on benchmark datasets. The simulation branch provides learning-based cryo-ET simulation for the first time and generates synthetic tomograms indistinguishable from experimental ones. Through comprehensive evaluations, we showcase the effectiveness of DUAL in detecting macromolecular complexes across a wide range of molecular weights in experimental datasets. The versatility of DUAL is expected to empower cryo-ET researchers by improving visual interpretability, enhancing structural detection accuracy, expediting annotation processes, facilitating cross-domain model adaptability, and compensating for missing wedge artifacts. Our work represents a significant advancement in the unsupervised mining of protein structures in cryo-ET, offering a multifaceted tool that facilitates cryo-ET research.

bioinformatics↗

bioRxiv2024

PFKP regulates AXL-MET oncogenic and metabolic pathways in lung cancer

ObjectivePFKP (Phosphofructokinase, Platelet Type isoform), as an essential metabolic enzyme, contributes to the high glycolysis rates seen in cancers, while its role in oncogenic pathways, especially from a non-metabolic aspect, is not fully understood. MethodsHere we performed a comprehensive analysis of published RNA-seq, microarray data, and immunohistochemistry of tissue microarray to evaluate the significance of PFKP expression in non-small cell lung cancer (NSCLC). Functionally, we tested the cell proliferation, colony formation, invasion, and migration upon PFKP knockdown in lung cancer cells. Mechanistically, we performed RNA-seq, DIA-mass spectrum, western blot, and qPCR to probe the change of cell signaling pathways upon PFKP silencing. Co-immunoprecipitation and mass spectrum were used to uncover potential PFKP interacting proteins. ResultsWe found that PFKP was highly expressed in NSCLC and was related to poor patient survival. Knockdown of PFKP significantly inhibited cell proliferation, colony formation, invasion, and migration of NSCLC cells. Mechanistically, we found that PFKP can directly bind with AXL and promote its phosphorylation at Y779, thus activating the AXL signaling pathway and promoting MET phosphorylation. In addition, several glycolysis, glutaminolysis, and TCA cycle proteins were downregulated following PFKP silencing. ConclusionsThese data demonstrate that PFKP, beyond its known role in glycolysis, also has a distinct non-metabolic function in affecting lung cancer progression by directly interacting with the AXL-MET axis, thus indicating a potential therapeutic target for lung cancer.

cancer biology↗

bioRxiv2024

Exploring the conformational space of protein-protein complex with transformer-based generative model

Protein-protein interactions are the basis of many protein functions, and understanding the contact and conformational changes of protein-protein interactions is crucial for linking protein structure to biological function. Although difficult to detect experimentally, molecular dynamics (MD) simulations are widely used to study the conformational ensembles and dynamics of protein-protein complexes, but there are significant limitations in sampling efficiency and computational costs. In this study, a generative neural network was trained on protein-protein complex conformations obtained from molecular simulations to directly generate novel conformations with physical realism. We demonstrated the use of a deep learning model based on the transformer architecture to explore the conformational ensembles of protein-protein complexes through MD simulations. The results showed that the learned latent space can be used to generate unsampled conformations of protein-protein complexes for obtaining new conformations complementing pre-existing ones, which can be used as an exploratory tool for the analysis and enhancement of molecular simulations of protein-protein complexes.

bioinformatics↗

bioRxiv2024

CLSTN3B enhances adipocyte lipid droplet structure and function via endoplasmic reticulum contact

Interorganelle contacts facilitate material exchanges and sustain the structural and functional integrity of organelles. Lipid droplets (LDs) of adipocytes are responsible for energy storage and mobilization responding to body needs. LD biogenesis defects compromise the lipid-storing capacity of adipocytes, resulting in ectopic lipid deposition and metabolic disorders, yet how the uniquely large LDs in adipocytes attain structural and functional maturation is incompletely understood. Here we show that the mammalian adipocyte-specific protein CLSTN3B is crucial for adipocyte LD maturation. CLSTN3B employs an arginine-rich segment to promote extensive contact and hemifusion-like structure formation between the endoplasmic reticulum (ER) and LD, allowing ER-to-LD phospholipid diffusion during LD expansion. CLSTN3B ablation results in reduced LD surface phospholipid density, increased turnover of LD-surface proteins, and impaired LD functions. Our results establish the central role of CLSTN3B in the adipocyte-specific LD maturation pathway that enhances lipid storage and maintenance of metabolic health under caloric overload.

cell biology↗

bioRxiv2024

Chemical imaging unveils mitochondria as the major site of medicinal biguanide accumulation within cells

Metformin (MET), a commonly prescribed medication for managing type 2 diabetes, has demonstrated various beneficial effects beyond its primary anti-diabetic efficacy. However, the mechanism underlying MET activity and its distribution within organelles remain largely unknown. In this study, we integrate multiple technologies, including chemical labeling, immunostaining, and high-resolution microscopy imaging, to visualize the accumulation of MET in organelles of cultured cells. To achieve this objective, an alkynylated MET probe is developed that preserves biological activity similar to biguanide drugs. As determined by biorthogonal chemical labeling and imaging, the MET probe selectively localizes to substructures within cells, contrasting with its probe control. Furthermore, the MET probe can be competitively and efficiently washed out through biguanide administration, demonstrating the specific activity of this probe in monitoring the cellular dynamics of biguanide drugs. Our results indicate that the MET probe can reach near-saturated concentrations within two hours and is rapidly eliminated within an additional two hours once the exogenous source of the drug is removed. Furthermore, we reveal that the MET probe primarily accumulates in mitochondria, particularly within the mitochondrial matrix, and has a minor presence in other organelles, such as lysosomes and endosomes. Together, this study provides the first view of the MET subcellular localization and lays the foundation for future investigations on its molecular targets and mechanisms of action in promoting human health.

molecular biology↗

bioRxiv2023

STAIG: Spatial Transcriptomics Analysis via Image-Aided Graph Contrastive Learning for Domain Exploration and Alignment-Free Integration

Spatial transcriptomics is an essential application for investigating cellular structures and interactions and requires multimodal information to precisely study spatial domains. Here, we propose STAIG, a novel deep-learning model that integrates gene expression, spatial coordinates, and histological images using graph-contrastive learning coupled with high-performance feature extraction. STAIG can integrate tissue slices without prealignment and remove batch effects. Moreover, it was designed to accept data acquired from various platforms, with or without histological images. By performing extensive benchmarks, we demonstrated the capability of STAIG to recognize spatial regions with high precision and uncover new insights into tumor microenvironments, highlighting its promising potential in deciphering spatial biological intricates.

bioinformatics↗