Clonal evolution from B-cell acute lymphoblastic leukemia with BCR::ABL1 multilineage involvement to acute myeloid leukemia after multiple anti-CD19 chimeric antigen receptor T-cell therapy.

Not available.

A Chromosome-Level Genome Assembly and Annotation for the Oecanthus rufescens (Orthoptera: Oecanthidae).

Oecanthus is a genus of cricket known for its distinctive chirping and distributed across major zoogeographical regions worldwide. This study focuses on Oecanthus rufescens, and conducts a comprehensive examination of its genome through genome sequencing technologies and bioinformatic analysis. A high-quality chromosome-level genome of O. rufescens was successfully obtained, revealing significant features of its genome structure. The genome size is 877.9 Mb, comprising 10 pseudo-chromosomes and 70 other sequences, with a GC content of 41.38% and an N50 value of 157,110,771 bp, indicating a high level of continuity. BUSCO assessment results demonstrate the genome's integrity and quality are high (of which 96.8% are single-copy and 1.6% are duplicated). Comprehensive genome annotation was also performed, identifying approximately 310 Mb of repetitive sequences, accounting for 35.3% of the total genome sequence, and discovering 15,481 tRNA genes, 4,082 rRNA genes, and 1,212 other non-coding genes. Furthermore, 15,031 protein-coding genes were identified, with BUSCO assessment results showing that 98.4% (of which 96.3% are single-copy and 1.6% are duplicated) of the genes were annotated.

Boosting the oxygen reduction activity of non-metallic catalysts via geometric and electronic engineering through nitrogen and chlorine dual-doping.

The development of heteroatom dual-doped porous carbon frameworks with uniform doping is highly desirable for achieving highly efficient oxygen reduction reaction (ORR) activity, due to their tunable chemical and electronic structures. Herein, porous covalent triazine-based frameworks (CTFs) incorporating nitrogen/chorine dual-doped porous carbon networks were fabricated by selecting 1,3-bis(4-cyanophenyl) imidazolium chloride as a building block, in a facile and controllable way via a bottom-up strategy. The resulting nitrogen/chorine dual-doped catalyst CCTF-700 exhibits excellent ORR performance with a more positive onset and half-wave potential (0.85 V vs. RHE), higher diffusion-limited current density and significantly improved stability in comparison with the benchmark commercial 20 wt% Pt/C catalyst. It is worth mentioning that CCTF-700 shows one of the best ORR performances among all the reported metal-free electrocatalysts under alkaline conditions. This work paves the way for a controllable and reliable strategy to craft highly efficient heteroatom dual-doped carbon catalysts for energy conversion.

Electron-Delocalization Across High Surface Entropy Sub-1 nm Nanobelts Toward Enhanced Electrocatalytic Urea Oxidation.

Integration of inherently incompatible elements into a single sublattice, resulting in the formation of monophasic metal oxide, holds great scientific promise; it unveils that the overlooked surface entropy in subnanometer materials can thermodynamically facilitate the formation of homogeneous single-phase structures. Here a facile approach is proposed for synthesizing multimetallic oxide subnanometer nanobelts (MMO-PMA SNBs) by harnessing the potential of phosphomolybdic acid (PMA) clusters to capture inorganic nuclei and inhibiting their subsequent growth in solvothermal reactions. Experimental and theoretical analyses show that PMA in MMO-PMA SNBs not only aids subnanometer structure formation but also induces in situ modifications to catalytic sites. The electron transfer from PMA, coupled with the loss of elemental identity of transition metals, leads to electron delocalization, jointly activating the reaction sites. The unique structure makes pentametallic oxide (PMO-PMA SNBs) achieve a current density of 10 mA cm-2 at a low potential of 1.34 V and remain stable for 24 h at 10 mA cm-2 on urea oxidation reaction (UOR). The exceptional UOR catalytic activity suggests a potential for utilizing multimetallic subnanometer nanostructures in energy conversion and environmental remediation.

Brain effect mechanism of lever positioning manipulation on LDH analgesia based on multimodal MRI: a study protocol.

INTRODUCTION: The clinical symptoms of Lumbar Disc Herniation (LDH) can be effectively ameliorated through Lever Positioning Manipulation (LPM), which is closely linked to the brain's pain-regulating mechanisms. Magnetic Resonance Imaging (MRI) offers an objective and visual means to study how the brain orchestrates the characteristics of analgesic effects. From the perspective of multimodal MRI, we applied functional MRI (fMRI) and Magnetic Resonance Spectrum (MRS) techniques to comprehensively evaluate the characteristics of the effects of LPM on the brain region of LDH from the aspects of brain structure, brain function and brain metabolism. This multimodal MRI technique provides a biological basis for the clinical application of LPM in LDH. METHODS AND ANALYSIS: A total of 60 LDH patients and 30 healthy controls, matched by gender, age, and years of education, will be enrolled in this study. The LDH patients will be divided into two groups (Group 1, n = 30; Group 2, n = 30) using a random number table method. Group 1 will receive LPM treatment once every two days, for a total of 12 times over 4 weeks. Group 2 will receive sham LPM treatment during the same period as Group 1. All 30 healthy controls will be divided into Group 3. Multimodal MRI will be performed on Group 1 and Group 2 at three time points (TPs): before LPM (TP1), after one LPM session (TP2), and after a full course of LPM treatment. The healthy controls (Group 3) will not undergo LPM and will be subject to only a single multimodal MRI scan. Participants in both Group 1 and Group 2 will be required to complete clinical questionnaires. These assessments will focus on pain intensity and functional disorders, using the Visual Analog Scale (VAS) and the Japanese Orthopaedic Association (JOA) scoring systems, respectively. DISCUSSION: The purpose of this study is to investigate the multimodal brain response characteristics of LDH patients after treatment with LPM, with the goal of providing a biological basis for clinical applications. TRIAL REGISTRATION NUMBER: https://clinicaltrials.gov/ct2/show/NCT05613179 , identifier: NCT05613179.

A Two-Pronged Delivery Strategy Disrupting Positive Feedback Loop of Neutrophil Extracellular Traps for Metastasis Suppression.

Neutrophil extracellular traps (NETs) severely affect tumor metastasis through a self-perpetuating feedback loop involving two key steps: (1) mitochondrial aerobic respiration-induced hypoxia promotes NET formation and (2) NETs enhance mitochondrial metabolism to exacerbate hypoxia. Herein, we propose a two-pronged approach with the activity of NET-degrading and mitochondrion-damaging by simultaneously targeting drugs to NETs and tumor mitochondria of this loop. In addition to specifically recognizing and eliminating extant NETs, the NET-targeting nanoparticle also reduces NET-induced mitochondrial biogenesis, thus inhibiting the initial step of the feedback loop and mitigating extant NETs' impact on tumor metastasis. Simultaneously, the mitochondrion-targeting system intercepts mitochondrial metabolism and alleviates tumor hypoxia, inhibiting neutrophil infiltration and subsequent NET formation, which reduces the source of NETs and disrupts another step of the self-amplifying feedback loop. Together, the combination significantly reduces the formation of NET-tumor cell clusters by disrupting the interaction between NETs and tumor mitochondria, thereby impeding the metastatic cascade including tumor invasion, hematogenous spread, and distant colonization. This work represents an innovative attempt to disrupt the feedback loop in tumor metastasis, offering a promising therapeutic approach restraining NET-assisted metastasis.

Promising dawn in the management of pulmonary hypertension: The mystery veil of gut microbiota.

The gut microbiota is a complex community of microorganisms inhabiting the intestinal tract, which plays a vital role in human health. It is intricately involved in the metabolism, and it also affects diverse physiological processes. The gut-lung axis is a bidirectional pathway between the gastrointestinal tract and the lungs. Recent research has shown that the gut microbiome plays a crucial role in immune response regulation in the lungs and the development of lung diseases. In this review, we present the interrelated factors concerning gut microbiota and the associated metabolites in pulmonary hypertension (PH), a lethal disease characterized by elevated pulmonary vascular pressure and resistance. Our research team explored the role of gut-microbiota-derived metabolites in cardiovascular diseases and established the correlation between metabolites such as putrescine, succinate, trimethylamine N-oxide (TMAO), and N, N, N-trimethyl-5-aminovaleric acid with the diseases. Furthermore, we found that specific metabolites, such as TMAO and betaine, have significant clinical value in PH, suggesting their potential as biomarkers in disease management. In detailing the interplay between the gut microbiota, their metabolites, and PH, we underscored the potential therapeutic approaches modulating this microbiota. Ultimately, we endeavor to alleviate the substantial socioeconomic burden associated with this disease. This review presents a unique exploratory analysis of the link between gut microbiota and PH, intending to propel further investigations in the gut-lung axis.

Identifying Veterans Who Benefit From Nirmatrelvir-Ritonavir: A Target Trial Emulation.

BACKGROUND: Nirmatrelvir-ritonavir is recommended for persons at risk for severe coronavirus disease 2019 (COVID-19) but remains underutilized. Information on which eligible groups are likely to benefit from treatment is needed. METHODS: We conducted a target trial emulation study in the Veterans Health Administration comparing nirmatrelvir-ritonavir treated versus matched untreated veterans at risk for severe COVID-19 who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from April 2022 through March 2023. We measured incidence of any hospitalization or all-cause mortality at 30 days. Outcomes were measured for the entire cohort, as well as among subgroups defined by 30-day risk of death or hospitalization, estimated using an ensemble risk prediction model. RESULTS: Participants were 87% male with median age 66 years and 16% unvaccinated. Compared with matched untreated participants, those treated with nirmatrelvir-ritonavir (n = 24 205) had a lower 30-day risk for hospitalization (1.80% vs 2.30%; risk difference [RD], -0.50% points [95% confidence interval {CI}: -.69 to -.35]) and death (0.11% vs 0.30%; RD, -0.20 [95% CI: -.24 to -.13]). The greatest reductions in combined hospitalization or death were observed in the highest risk quartile (RD -2.85 [95% CI: -3.94 to -1.76]), immunocompromised persons (RD -1.91 [95% CI: -3.09 to -.74]), and persons aged ≥75 years (RD -1.16 [95% CI: -1.73 to -.59]). No reductions were observed in the 2 lowest risk quartiles or persons younger than 65 years. CONCLUSIONS: Nirmatrelvir-ritonavir was effective in reducing 30-day hospitalization and death in older veterans, those at highest predicted risk for severe outcomes, and immunocompromised groups. Benefit was not observed in younger veterans or groups at lower predicted risk for hospitalization and death.

Manipulation of Moiré Superlattice in Twisted Monolayer-multilayer Graphene by Moving Nanobubbles.

In the heterostructure of two-dimensional (2D) materials, many novel physics phenomena are strongly dependent on the Moiré superlattice. How to achieve the continuous manipulation of the Moiré superlattice in the same sample is very important to study the evolution of various physical properties. Here, in minimally twisted monolayer-multilayer graphene, we found that bubble-induced strain has a huge impact on the Moiré superlattice. By employing the AFM tip to dynamically and continuously move the nanobubble, we realized the modulation of the Moiré superlattice, like the evolution of regular triangular domains into long strip domain structures with single or double domain walls. We also achieved controllable modulation of the Moiré superlattice by moving multiple nanobubbles and establishing the coupling of nanobubbles. Our work presents a flexible method for continuous and controllable manipulation of Moiré superlattices, which will be widely used to study novel physical properties in 2D heterostructures.

FOXCUT regulates the malignant phenotype of triple-negative breast Cancer via the miR-337-3p/ANP32E Axis.

BACKGROUND: The lack of specific molecular targets and the rapid spread lead to a worse prognosis of triple-negative breast cancer (TNBC). Therefore, identifying new therapeutic and prognostic biomarkers helps to develop effective treatment strategies for TNBC. METHODS: Through preliminary bioinformatics analysis, FOXCUT was found to be significantly overexpressed in breast cancer, especially in TNBC. Tissue samples were collected from 15 TNBC patients, and qRT-PCR was employed to validate the expression of FOXCUT in both TNBC patient tissues and TNBC cell lines. We also carried out the GSEA analysis and KEGG enrichment analysis of FOXCUT. Additionally, the effects of FOXCUT knockdown on TNBC cell malignant behaviors, and aerobic glycolysis were assessed by methods including CCK-8, Transwell, western blot, and Seahorse XF 96 analyses. Moreover, utilizing databases predicting interactions between ceRNAs, corresponding lncRNA-miRNA binding relationships, and miRNA-mRNA interactions were predicted. These predictions were subsequently validated through RNA immunoprecipitation and dual-luciferase reporter assays. RESULTS: FOXCUT exhibited high expression in both TNBC tissues and cell lines, fostering cell malignant behaviors and glycolysis. FOXCUT was found to sponge miR-337-3p, while miR-337-3p negatively regulated the expression of ANP32E. Consequently, FOXCUT ultimately facilitated the malignant phenotype of TNBC by upregulating ANP32E expression. CONCLUSION: This study elucidated the role of FOXCUT in elevating aerobic glycolysis levels in TNBC and driving malignant cancer cell development via the miR-337-3p/ANP32E regulatory axis.

Enhanced flotation removal of polystyrene nanoplastics by chitosan modification: Performance and mechanism.

Nanoplastics are difficult to remove from water using conventional flotation processes due to their stability and resistance to biodegradation. Here, polystyrene nanoplastics (PSNPs) were selected as the object of study. In addition, chitosan (CTS), an environmentally friendly natural cationic polymer, was selected to modify the air flotation process to improve the separation of PSNPs using air flotation. Adding chitosan effectively enhanced the removal of PSNPs using air flotation from 3.1 % to 96.7 %. The residual concentration decreased from 9.69 mg/L to 0.33 mg/L. Removal of PSNPs by CTS-modified air flotation was maintained at 92.8 % even when the air flotation time was significantly shortened. The zeta potential alterations demonstrated robust electrostatic attraction within the CTS-modified air flotation process. The contact angle measurements indicated that incorporating CTS could enhance the hydrophobic interaction between bubbles and PSNPs. PSNPs particles around 100 nm agglomerated to form floating flocs with a particle size of more than 4500 nm. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) images confirmed the presence of tight adhesion between PSNPs and CTS, indicating the presence of bridging adsorption during the process. The major PSNPs removal mechanisms included electrostatic attraction, enhancement of hydrophobicity, and bridging adsorption. Increasing the aeration volume could improve the removal rate, but this improvement was finite. Weakly acidic and low ionic strength conditions favored PSNPs removal. The CTS-modified air flotation process showed great potential for PSNPs removal from real water bodies.

Weathering the storm: diagnosis and treatment of a life-threatening disseminated Nocardia otitidiscaviarum infection.

Nocardiosis demonstrates a temporal categorization that includes acute, subacute, and chronic stages alongside distinct typical localizations such as pulmonary, cutaneous, and disseminated forms. Disseminated nocardiosis, commonly caused by Nocardia asteroides, N. brasiliensis, and N. farcinica, continues to result in substantial morbidity and mortality. Herein, we report a life-threatening disseminated nocardiosis caused by Nocardia otitidiscaviarum in a patient with minimal change disease. This study emphasizes the difficulty in the diagnosis and treatment of unknown infections in clinical settings and highlights the important role played by laboratories in solving infectious diseases caused by rare pathogens.

A lumped parameter model for evaluating coronary artery blood supply capacity.

The coronary artery constitutes a vital vascular system that sustains cardiac function, with its primary role being the conveyance of indispensable nutrients to the myocardial tissue. When coronary artery disease occurs, it will affect the blood supply of the heart and induce myocardial ischemia. Therefore, it is of great significance to numerically simulate the coronary artery and evaluate its blood supply capacity. In this article, the coronary artery lumped parameter model was derived based on the relationship between circuit system parameters and cardiovascular system parameters, and the blood supply capacity of the coronary artery in healthy and stenosis states was studied. The aortic root pressure calculated by the aortic valve fluid-structure interaction (AV FSI) simulator was employed as the inlet boundary condition. To emulate the physiological phenomenon of sudden pressure drops resulting from an abrupt reduction in blood vessel radius, a head loss model was connected at the coronary artery's entrance. For each coronary artery outlet, the symmetric structured tree model was appended to simulate the terminal impedance of the missing downstream coronary arteries. The particle swarm optimization (PSO) algorithm was used to optimize the blood flow viscous resistance, blood flow inertia, and vascular compliance of the coronary artery model. In the stenosis states, the relative flow and fractional flow reserve (FFR) calculated by numerical simulation corresponded to the published literature data. It was anticipated that the proposed model can be readily adapted for clinical application, serving as a valuable reference for diagnosing and treating patients.

Integrated analysis of multiple transcriptomic approaches and machine learning integration algorithms reveals high endothelial venules as a prognostic immune-related biomarker in bladder cancer.

BACKGROUND: Despite the availability of established surgical and chemotherapy options, the treatment of bladder cancer (BCa) patients remains challenging. While immunotherapy has emerged as a promising approach, its benefits are limited to a subset of patients. The exploration of additional targets to enhance the efficacy of immunotherapy is a valuable research direction. METHOD: High endothelial venules (HEV) ssGSEA analysis was conducted using BEST. Through the utilization of R packages Limma, Seurat, SingleR, and Harmony, analyses were performed on spatial transcriptomics, bulk RNA-sequencing (bulk RNA-seq), and single-cell RNA sequencing (scRNA-seq) data, yielding HEV-related genes (HEV.RGs). Molecular subtyping analysis based on HEV.RGs was conducted using R package MOVICS, and various machine learning-integrated algorithm was employed to construct prognostic model. LDLRAD3 was validated through subcutaneous tumor formation in mice, HEV induction, Western blot, and qPCR. RESULTS: A correlation between higher HEV levels and improved immune response and prognosis was revealed by HEV ssGSEA analysis in BCa patients receiving immunotherapy. HEV.RGs were identified in subsequent transcriptomic analyses. Based on these genes, BCa patients were stratified into two molecular clusters with distinct survival and immune infiltration patterns using various clustering-integrated algorithm. Prognostic model was developed using multiple machine learning-integrated algorithm. Low LDLRAD3 expression may promote HEV generation, leading to enhanced immunotherapy efficacy, as suggested by bulk RNA-seq, scRNA-seq analyses, and experimental validation of LDLRAD3. CONCLUSIONS: HEV served as a predictive factor for immune response and prognosis in BCa patients receiving immunotherapy. LDLRAD3 represented a potential target for HEV induction and enhancing the efficacy of immunotherapy.

Cardiovascular disease therapeutics via engineered oral microbiota: Applications and perspective.

Engineering bacteria are considered as a potential treatment for cardiovascular diseases and related risk factors. Oral bacteria are closely related to the occurrence and development of cardiovascular diseases, and their engineering has broad prospects and potential in the treatment of cardiovascular diseases. Oral pathogenic bacteria undergo protein and genetic engineering, including the incorporation of exogenous plasmids to yield therapeutic effects; genetically engineered oral probiotics can be harnessed to secrete cytokines and reactive oxygen species, offering novel therapeutic avenues for cardiovascular diseases.

Biped Robots Control in Gusty Environments with Adaptive Exploration Based DDPG.

As technology rapidly evolves, the application of bipedal robots in various environments has widely expanded. These robots, compared to their wheeled counterparts, exhibit a greater degree of freedom and a higher complexity in control, making the challenge of maintaining balance and stability under changing wind speeds particularly intricate. Overcoming this challenge is critical as it enables bipedal robots to sustain more stable gaits during outdoor tasks, thereby increasing safety and enhancing operational efficiency in outdoor settings. To transcend the constraints of existing methodologies, this research introduces an adaptive bio-inspired exploration framework for bipedal robots facing wind disturbances, which is based on the Deep Deterministic Policy Gradient (DDPG) approach. This framework allows the robots to perceive their bodily states through wind force inputs and adaptively modify their exploration coefficients. Additionally, to address the convergence challenges posed by sparse rewards, this study incorporates Hindsight Experience Replay (HER) and a reward-reshaping strategy to provide safer and more effective training guidance for the agents. Simulation outcomes reveal that robots utilizing this advanced method can more swiftly explore behaviors that contribute to stability in complex conditions, and demonstrate improvements in training speed and walking distance over traditional DDPG algorithms.

In vitro and in vivo studies on exogenous polyamines and α-difluoromethylornithine to enhance bone formation and suppress osteoclast differentiation.

Exogenous polyamines, including putrescine (PUT), spermidine (SPD), and spermine (SPM), and the irreversible inhibitor of the rate-limiting enzyme ornithine decarboxylase (ODC) of polyamine biosynthesis, α-difluoromethylornithine (DFMO), are implicated as stimulants for bone formation. We demonstrate in this study the osteogenic potential of exogenous polyamines and DFMO in human osteoblasts (hOBs), murine monocyte cell line RAW 264.7, and an ovariectomized rat model. The effect of polyamines and DFMO on hOBs and RAW 264.7 cells was studied by analyzing gene expression, alkaline phosphatase (ALP) activity, tartrate-resistant acid phosphatase (TRAP) activity, and matrix mineralization. Ovariectomized rats were treated with polyamines and DFMO and analyzed by micro computed tomography (micro CT). The mRNA level of the early onset genes of osteogenic differentiation, Runt-related transcription factor 2 (Runx2) and ALP, was significantly elevated in hOBs under osteogenic conditions, while both ALP activity and matrix mineralization were enhanced by exogenous polyamines and DFMO. Under osteoclastogenic conditions, the gene expression of both receptor activator of nuclear factor-κB (RANK) and nuclear factor of activated T-cells, cytoplasmic 1 (NFATc1) was reduced, and TRAP activity was suppressed by exogenous polyamines and DFMO in RAW 264.7 cells. In an osteoporotic animal model of ovariectomized rats, SPM and DFMO were found to improve bone volume in rat femurs, while trabecular thickness was increased in all treatment groups. Results from this study provide in vitro and in vivo evidence indicating that polyamines and DFMO act as stimulants for bone formation, and their osteogenic effect may be associated with the suppression of osteoclastogenesis.

Fast and High-Resolution T2 Mapping Based on Echo Merging Plus k-t Undersampling with Reduced Refocusing Flip Angles (TEMPURA) as Methods for Human Renal MRI.

PURPOSE: To develop a highly accelerated multi-echo spin-echo method, TEMPURA, for reducing the acquisition time and/or increasing spatial resolution for kidney T2 mapping. METHODS: TEMPURA merges several adjacent echoes into one k-space by either combining independent echoes or sharing one echo between k-spaces. The combined k-space is reconstructed based on compressed sensing theory. Reduced flip angles are used for the refocusing pulses, and the extended phase graph algorithm is used to correct the effects of indirect echoes. Two sequences were developed: a fast breath-hold sequence; and a high-resolution sequence. The performance was evaluated prospectively on a phantom, 16 healthy subjects, and two patients with different types of renal tumors. RESULTS: The fast TEMPURA method reduced the acquisition time from 3-5 min to one breath-hold (18 s). Phantom measurements showed that fast TEMPURA had a mean absolute percentage error (MAPE) of 8.2%, which was comparable to a standardized respiratory-triggered sequence (7.4%), but much lower than a sequence accelerated by purely k-t undersampling (21.8%). High-resolution TEMPURA reduced the in-plane voxel size from 3 × 3 to 1 × 1 mm2, resulting in improved visualization of the detailed anatomical structure. In vivo T2 measurements demonstrated good agreement (fast: MAPE = 1.3%-2.5%; high-resolution: MAPE = 2.8%-3.3%) and high correlation coefficients (fast: R = 0.85-0.98; high-resolution: 0.82-0.96) with the standardized method, outperforming k-t undersampling alone (MAPE = 3.3-4.5%, R = 0.57-0.59). CONCLUSION: TEMPURA provides fast and high-resolution renal T2 measurements. It has the potential to improve clinical throughput and delineate intratumoral heterogeneity and tissue habitats at unprecedented spatial resolution.

Graph-Regularized Non-Negative Matrix Factorization for Single-Cell Clustering in scRNA-Seq Data.

The advent of single-cell RNA sequencing (scRNA-seq) has brought forth fresh perspectives on intricate biological processes, revealing the nuances and divergences present among distinct cells. Accurate single-cell analysis is a crucial prerequisite for in-depth investigation into the underlying mechanisms of heterogeneity. Due to various technical noises, like the impact of dropout values, scRNA-seq data remains challenging to interpret. In this work, we propose an unsupervised learning framework for scRNA-seq data analysis (aka Sc-GNNMF). Based on the non-negativity and sparsity of scRNA-seq data, we propose employing graph-regularized non-negative matrix factorization (GNNMF) algorithm for the analysis of scRNA-seq data, which involves estimating cell-cell similarity and gene-gene similarity through Laplacian kernels and p-nearest neighbor graphs ( p-NNG). By assuming intrinsic geometric local invariance, we use a weighted p-nearest known neighbors ( p-NKN) of cell-cell interactions to guide the matrix decomposition process, promoting the closeness of cells with similar types in cell-gene data space and determining a more suitable embedding space for clustering. Sc-GNNMF demonstrates superior performance compared to other methods and maintains satisfactory compatibility and robustness, as evidenced by experiments on 11 real scRNA-seq datasets. Furthermore, Sc-GNNMF yields excellent results in clustering tasks, extracting useful gene markers, and pseudo-temporal analysis.