Pseudomonas paeninsulae sp. nov. and Pseudomonas svalbardensis sp. nov., isolated from Antarctic intertidal sediment and Arctic soil, respectively.

Two Gram-stain-negative, aerobic, rod-shaped, non-endospore-forming and motile bacterial strains, designated IT1137T and S025T, were isolated from an intertidal sediment sample collected from the Fildes Peninsula (King George Island, Maritime Antarctica) and a soil sample under red snow in the Ny-Ålesund region (Svalbard, High Arctic), respectively. The 16S rRNA gene sequence similarity values grouped them in the genus Pseudomonas. The two strains were characterized phenotypically using API 20E, API 20NE, API ZYM and Biolog GENIII tests and chemotaxonomically by their fatty acid contents, polar lipids and respiratory quinones. Multilocus sequence analysis (concatenated 16S rRNA, gyrB, rpoB and rpoD sequences), together with genome comparisons by average nucleotide identity and digital DNA-DNA hybridization, were performed. The results showed that the similarity values of the two isolates with the type strains of related Pseudomonas species were below the recognized thresholds for species definition. Based on polyphasic taxonomy analysis, it can be concluded that strains IT1137T and S025T represent two novel species of the genus Pseudomonas, for which the names Pseudomonas paeninsulae sp. nov. (type strain IT1137T=PMCC 100533T=CCTCC AB 2023226T=JCM 36637T) and Pseudomonas svalbardensis sp. nov. (type strain S025T=PMCC 200367T= CCTCC AB 2023225T=JCM 36638T) are proposed.

Development and Validation of an Interpretable Machine Learning Model for Early Prognosis Prediction in ICU Patients with Malignant Tumors and Hyperkalemia.

This study aims to develop and validate a machine learning (ML) predictive model for assessing mortality in patients with malignant tumors and hyperkalemia (MTH). We extracted data on patients with MTH from the Medical Information Mart for Intensive Care-IV, version 2.2 (MIMIC-IV v2.2) database. The dataset was split into a training set (75%) and a validation set (25%). We used the Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify potential predictors, which included clinical laboratory indicators and vital signs. Pearson correlation analysis tested the correlation between predictors. In-hospital death was the prediction target. The Area Under the Curve (AUC) and accuracy of the training and validation sets of 7 ML algorithms were compared, and the optimal 1 was selected to develop the model. The calibration curve was used to evaluate the prediction accuracy of the model further. SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) enhanced model interpretability. 496 patients with MTH in the Intensive Care Unit (ICU) were included. After screening, 17 clinical features were included in the construction of the ML model, and the Pearson correlation coefficient was <0.8, indicating that the correlation between the clinical features was small. eXtreme Gradient Boosting (XGBoost) outperformed other algorithms, achieving perfect scores in the training set (accuracy: 1.000, AUC: 1.000) and high scores in the validation set (accuracy: 0.734, AUC: 0.733). The calibration curves indicated good predictive calibration of the model. SHAP analysis identified the top 8 predictive factors: urine output, mean heart rate, maximum urea nitrogen, minimum oxygen saturation, minimum mean blood pressure, maximum total bilirubin, mean respiratory rate, and minimum pH. In addition, SHAP and LIME performed in-depth individual case analyses. This study demonstrates the effectiveness of ML methods in predicting mortality risk in ICU patients with MTH. It highlights the importance of predictors like urine output and mean heart rate. SHAP and LIME significantly enhanced the model's interpretability.

Identification of Two Potential Gene Insertion Sites for Gene Editing on the Chicken Z/W Chromosomes.

The identification of accurate gene insertion sites on chicken sex chromosomes is crucial for advancing sex control breeding materials. In this study, the intergenic region NC_006127.4 on the chicken Z chromosome and the non-repetitive sequence EE0.6 on the W chromosome were selected as potential gene insertion sites. Gene knockout vectors targeting these sites were constructed and transfected into DF-1 cells. T7E1 enzyme cleavage and luciferase reporter enzyme analyses revealed knockout efficiencies of 80.00% (16/20), 75.00% (15/20), and 75.00% (15/20) for the three sgRNAs targeting the EE0.6 site. For the three sgRNAs targeting the NC_006127.4 site, knockout efficiencies were 70.00% (14/20), 60.00% (12/20), and 45.00% (9/20). Gel electrophoresis and high-throughput sequencing were performed to detect potential off-target effects, showing no significant off-target effects for the knockout vectors at the two sites. EdU and CCK-8 proliferation assays revealed no significant difference in cell proliferation activity between the knockout and control groups. These results demonstrate that the EE0.6 and NC_006127.4 sites can serve as gene insertion sites on chicken sex chromosomes for gene editing without affecting normal cell proliferation.

Reinforcement learning for individualized lung cancer screening schedules: A nested case-control study.

BACKGROUND: The current guidelines for managing screen-detected pulmonary nodules offer rule-based recommendations for immediate diagnostic work-up or follow-up at intervals of 3, 6, or 12 months. Customized visit plans are lacking. PURPOSE: To develop individualized screening schedules using reinforcement learning (RL) and evaluate the effectiveness of RL-based policy models. METHODS: Using a nested case-control design, we retrospectively identified 308 patients with cancer who had positive screening results in at least two screening rounds in the National Lung Screening Trial. We established a control group that included cancer-free patients with nodules, matched (1:1) according to the year of cancer diagnosis. By generating 10,164 sequence decision episodes, we trained RL-based policy models, incorporating nodule diameter alone, combined with nodule appearance (attenuation and margin) and/or patient information (age, sex, smoking status, pack-years, and family history). We calculated rates of misdiagnosis, missed diagnosis, and delayed diagnosis, and compared the performance of RL-based policy models with rule-based follow-up protocols (National Comprehensive Cancer Network guideline; China Guideline for the Screening and Early Detection of Lung Cancer). RESULTS: We identified significant interactions between certain variables (e.g., nodule shape and patient smoking pack-years, beyond those considered in guideline protocols) and the selection of follow-up testing intervals, thereby impacting the quality of the decision sequence. In validation, one RL-based policy model achieved rates of 12.3% for misdiagnosis, 9.7% for missed diagnosis, and 11.7% for delayed diagnosis. Compared with the two rule-based protocols, the three best-performing RL-based policy models consistently demonstrated optimal performance for specific patient subgroups based on disease characteristics (benign or malignant), nodule phenotypes (size, shape, and attenuation), and individual attributes. CONCLUSIONS: This study highlights the potential of using an RL-based approach that is both clinically interpretable and performance-robust to develop personalized lung cancer screening schedules. Our findings present opportunities for enhancing the current cancer screening system.

Progressive Neighbor-masked Contrastive Learning for Fusion-style Deep Multi-view Clustering.

Fusion-style Deep Multi-view Clustering (FDMC) can efficiently integrate comprehensive feature information from latent embeddings of multiple views and has drawn much attention recently. However, existing FDMC methods suffer from the interference of view-specific information for fusion representation, affecting the learning of discriminative cluster structure. In this paper, we propose a new framework of Progressive Neighbor-masked Contrastive Learning for FDMC (PNCL-FDMC) to tackle the aforementioned issues. Specifically, by using neighbor-masked contrastive learning, PNCL-FDMC can explicitly maintain the local structure during the embedding aggregation, which is beneficial to the common semantics enhancement on the fusion view. Based on the consistent aggregation, the fusion view is further enhanced by diversity-aware cluster structure enhancement. In this process, the enhanced cluster assignments and cluster discrepancies are employed to guide the weighted neighbor-masked contrastive alignment of semantic structure between individual views and the fusion view. Extensive experiments validate the effectiveness of the proposed framework, revealing its ability in discriminative representation learning and improving clustering performance.

Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering.

Mutations in amino acid sequences can provoke changes in protein function. Accurate and unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but remains a fundamental challenge. To resolve this challenge, here we present Protein Mutational Effect Predictor (ProMEP), a general and multiple sequence alignment-free method that enables zero-shot prediction of mutation effects. A multimodal deep representation learning model embedded in ProMEP was developed to comprehensively learn both sequence and structure contexts from ~160 million proteins. ProMEP achieves state-of-the-art performance in mutational effect prediction and accomplishes a tremendous improvement in speed, enabling efficient and intelligent protein engineering. Specifically, ProMEP accurately forecasts mutational consequences on the gene-editing enzymes TnpB and TadA, and successfully guides the development of high-performance gene-editing tools with their engineered variants. The gene-editing efficiency of a 5-site mutant of TnpB reaches up to 74.04% (vs 24.66% for the wild type); and the base editing tool developed on the basis of a TadA 15-site mutant (in addition to the A106V/D108N double mutation that renders deoxyadenosine deaminase activity to TadA) exhibits an A-to-G conversion frequency of up to 77.27% (vs 69.80% for ABE8e, a previous TadA-based adenine base editor) with significantly reduced bystander and off-target effects compared to ABE8e. ProMEP not only showcases superior performance in predicting mutational effects on proteins but also demonstrates a great capability to guide protein engineering. Therefore, ProMEP enables efficient exploration of the gigantic protein space and facilitates practical design of proteins, thereby advancing studies in biomedicine and synthetic biology.

Recombinant Human Hepatocyte Growth Factor Plasmids for Treating Patients with Chronic Limb Threatening Ischaemia: A Systematic Review and Meta-analysis.

OBJECTIVE: Recombinant human hepatocyte growth factor (HGF) plasmids are novel alternatives to salvage limbs in patients with chronic limb threatening ischaemia (CLTI). A systematic review and meta-analysis of data were conducted to assess the therapeutic efficacy of HGF plasmids in patients with CLTI. DATA SOURCES: Randomised controlled studies evaluating HGF plasmid efficacy in patients with CLTI were identified using Medline, Embase, Cochrane Database of Systematic Reviews, and ClinicalTrials.gov databases. REVIEW METHODS: Meta-analyses of the reported relative risks (RR) or mean differences (MD) were conducted. Subgroup analyses determined the efficacy of HGF plasmids in cohorts excluding Buerger's disease. Certainty of evidence for each outcome was assessed. RESULTS: Seven studies (n = 655) were included. Based on low certainty evidence, patients treated with HGF had a significantly higher complete ulcer healing rate (RR 1.99, 95% CI 1.30 - 3.04; p = .015) than patients treated with placebo. The HGF treatment was associated with reduced visual analogue scale (VAS) scores of pain severity (MD -1.56, 95% CI -2.12 - -1.00; p < .001) vs. placebo in patients with CLTI assessed at the 3 month follow up (low certainty evidence); no significant differences were observed in major amputation (RR 0.91, 95% CI 0.48 - 1.73; p = .77) (low certainty evidence), or all-cause mortality (RR 0.93, 95% CI 0.38 - 2.27; p = .87) (low certainty evidence) between patients treated with HGF and placebo. Low certainty evidence suggested no significant differences in change in ankle-brachial index at 6 months (MD 0.00, 95% CI -0.09 - 0.09; p = 1.0) between patients treated with HGF and placebo. The complete ulcer healing rate and improved 3 month VAS scores of pain severity benefits persisted in subgroup analyses (low certainty evidence). CONCLUSION: Hepatocyte growth factor treatment is associated with an increased complete ulcer healing rate and reduced ischaemic pain in patients with CLTI.

Complete genome sequence of a novel Pseudomonas sp. IT1137 isolated from Antarctic intertidal sediment showing potential for alkane degradation at low temperatures.

Pseudomonas species are known for their diverse metabolic abilities and broad ecological distribution. They are fundamental components of bacterial communities and perform essential ecological functions in the environment. A psychrotrophic Pseudomonas sp. IT1137 was isolated from intertidal sediment in the coastal region of the Fildes Peninsula, King George Island, Antarctica. The strain contained a circular chromosome of 5,346,697 bp with a G + C content of 61.66 mol% and one plasmid of 4481 bp with a G + C content of 64.61 mol%. A total of 4848 protein-coding genes, 65 tRNA genes and 15 rRNA genes were obtained. Genome sequence analysis revealed that strain IT1137 not only is a potentially novel species of the genus Pseudomonas but also harbors functional genes related to nitrogen, sulfur and phosphorus cycling. In addition, genes involved in alkane degradation, ectoine synthesis and cyclic lipopeptide (CLP) production were detected in the bacterial genome. The results indicate the potential of the strain Pseudomonas sp. IT1137 for biotechnological applications such as bioremediation and secondary metabolite production and are helpful for understanding bacterial adaptability and ecological function in cold coastal environments.

[Discussion on reference sample research of traditional Chinese medicine compound preparations developed from catalogued ancient classical prescriptions].

The concept of reference sample was put forward in the Guidance on CMC of Traditional Chinese Medicine Compound Preparations Developed from Catalogued Ancient Classical Prescriptions(Interim). The research on reference sample is a key link in the research and development of traditional Chinese medicine(TCM) compound prescriptions from catalogued ancient classical prescriptions(known as Category 3.1 TCM). This paper discusses the content of research on reference sample by analyzing the characteristics of Category 3.1 TCM and the purpose of research on reference sample. Furthermore, suggestions on the research of reference sample are proposed according to the development and evaluation practice of Category 3.1 TCM and research achievements of TCM regulatory science, aiming to provide reference for colleagues in this industry.

Cardiac-derived extracellular vesicles improve mitochondrial function to protect the heart against ischemia/reperfusion injury by delivering ATP5a1.

BACKGROUND: Numerous studies have confirmed the involvement of extracellular vesicles (EVs) in various physiological processes, including cellular death and tissue damage. Recently, we reported that EVs derived from ischemia-reperfusion heart exacerbate cardiac injury. However, the role of EVs from healthy heart tissue (heart-derived EVs, or cEVs) on myocardial ischemia-reperfusion (MI/R) injury remains unclear. RESULTS: Here, we demonstrated that intramyocardial administration of cEVs significantly enhanced cardiac function and reduced cardiac damage in murine MI/R injury models. cEVs treatment effectively inhibited ferroptosis and maintained mitochondrial homeostasis in cardiomyocytes subjected to ischemia-reperfusion injury. Further results revealed that cEVs can transfer ATP5a1 into cardiomyocytes, thereby suppressing mitochondrial ROS production, alleviating mitochondrial damage, and inhibiting cardiomyocyte ferroptosis. Knockdown of ATP5a1 abolished the protective effects of cEVs. Furthermore, we found that the majority of cEVs are derived from cardiomyocytes, and ATP5a1 in cEVs primarily originates from cardiomyocytes of the healthy murine heart. Moreover, we demonstrated that adipose-derived stem cells (ADSC)-derived EVs with ATP5a1 overexpression showed much better efficacy on the therapy of MI/R injury compared to control ADSC-derived EVs. CONCLUSIONS: These findings emphasized the protective role of cEVs in cardiac injury and highlighted the therapeutic potential of targeting ATP5a1 as an important approach for managing myocardial damage induced by MI/R injury.

The mechanisms of Porphyromonas gingivalis-derived outer membrane vesicles-induced neurotoxicity and microglia activation.

Background/purpose: Periodontitis is associated with various systemic diseases, potentially facilitated by the passage of Porphyromonas gingivalis outer membrane vesicles (Pg-OMVs). Several recent studies have suggested a connection between Pg-OMVs and neuroinflammation and neurodegeneration, but the precise causal relationship remains unclear. This study aimed to investigate the mechanisms underlying these associations using in vitro models. Materials and methods: Isolated Pg-OMVs were characterized by morphology, size, and gingipain activity. We exposed SH-SY5Y neuroblastoma cells and BV-2 microglial cells to various concentrations of Pg-OMVs. Cell morphology, a 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, an enzyme-linked immunosorbent assay, and Western blot analysis were used to evaluate the cellular mechanism underlying Pg-OMV-induced neurotoxicity in neuronal cells and inflammatory responses in microglial cells. Results: Exposure to Pg-OMVs induced neurotoxicity in SH-SY5Y cells, as evidenced by cellular shrinkage, reduced viability, activation of apoptotic pathways, and diminished neuronal differentiation markers. Gingipain inhibition mitigated these effects, suggesting that gingipain mediates Pg-OMVs-induced neurotoxicity in SH-SY5Y cells. Our research on neuroinflammation suggests that upon endocytosis of Pg-OMVs by BV-2 cells, lipopolysaccharide (LPS) can modulate the production of inducible nitric oxide synthase and tumor necrosis factor-alpha by activating pathways that involve phosphorylated AKT and the phosphorylated JNK pathway. Conclusion: Our study demonstrated that following the endocytosis of Pg-OMVs, gingipain can induce neurotoxicity in SH-SY5Y cells. Furthermore, the Pg-OMVs-associated LPS can trigger neuroinflammation via AKT and JNK signaling pathways in BV-2 cells.

Mechanism underlying the role of integrin α3ß1 in adhesive dysfunction between thyroid cells induced by diesel engine exhaust particles.

The role and mechanisms of DEP exposure on thyroid injury are not yet clear. This study explores thyroid damage induced by in vivo DEP exposure using a mouse model. This study has observed alterations in thyroid follicular architecture, including rupture, colloid overflow, and the formation of voids. Additionally, there was a significant decrease in the expression levels of proteins involved in thyroid hormone synthesis, such as thyroid peroxidase and thyroglobulin, their trend of change is consistent with the damage to the thyroid structure. Serum levels of triiodothyronine and tetraiodothyronine were raise. However, the decrease in TSH expression suggests that the function of the HPT axis is unaffected. To delve deeper into the intrinsic mechanisms of thyroid injury, we performed KEGG pathway enrichment analysis, which revealed notable alterations in the cell adhesion signaling pathway. Our immunofluorescence results show that DEP exposure impairs thyroid adhesion, and integrin α3ß1 plays an important role. CD151 binds to α3ß1, promoting multimolecular complex formation and activating adhesion-dependent small GTPases. Our in vitro model has confirmed the pivotal role of integrin α3ß1 in thyroid cell adhesion, which may be mediated by the CD151/α3ß1/Rac1 pathway. In summary, exposure to DEP disrupts the structure and function of the thyroid, a process that likely involves the regulation of cell adhesion through the CD151/α3ß1/Rac1 pathway, leading to glandular damage.

Silver-Promoted Three-Component Synthesis of Perfluoroalkenyl Pyrroles through Partial Defluorinative Functionalization of Perfluoroalkyl Halides.

A silver-promoted three-component heterocyclization of alkynes, perfluoroalkyl halides, and 1,3-dinucleophiles was developed for the efficient synthesis of privileged (E)-perfluoroalkenyl pyrroles. The reaction proceeded through a rationally designed sequence of radical perfluoroalkylation and intramolecular defluorinative [3 + 2]-heterocyclization. The utility of perfluoroalkyl halide as a perfluoroalkenyl reagent, by selective and controllable functionalization of two inert C(sp3)-F bonds at vicinal carbon centers on the perfluoroalkyl chain, provides a new reaction mode for the synthesis of value-added organofluorides starting from the easily available and low-cost fluorinated feedstock.

Comprehensive analysis of aberrantly methylated differentially expressed genes and validation of CDC6 in melanoma.

BACKGROUND: Skin Cutaneous Melanoma (SKCM) is a highly aggressive malignant tumor with a significant increase in mortality upon metastasis. The molecular mechanisms driving melanoma progression remain largely unclear. Recent studies have highlighted the importance of epigenetic alterations, especially DNA methylation, in melanoma development. This study aims to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) in genome-wide profiles between primary and metastatic melanoma. METHODS: Gene expression profiling datasets GSE8401 and gene methylation profiling datasets GSE86355 were collected from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were systematically identified. Integration of DEGs and DMGs yielded a set of MeDEGs, which subsequently underwent functional enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING and visualized using Cytoscape software. Survival analysis was used to select prognostic hub genes. In addition, 37 SKCM and 37 normal skin tissues from the First Affiliated Hospital of Soochow University (FAHSU) were collected for immunohistochemical (IHC) staining and evaluation. Furthermore, DNA methylation patterns of CDC6 were analyzed. To validate these findings, SKCM cell cultures were utilized to elucidate the expression and behavioral characteristics of CDC6. Additionally, gene set enrichment analysis (GSEA) and immune infiltration analysis were conducted for CDC6. RESULTS: In our study, we discovered 120 hypomethylated-upregulated genes and 212 hypermethylated-downregulated genes. The hypomethylated-upregulated genes were notably associated with biological processes such as spindle assembly checkpoint signaling, mitotic spindle assembly, and negative regulation of mitotic metaphase/anaphase transition. Our pathway analysis revealed significant enrichment in pathways related to dilated cardiomyopathy, amino sugar metabolism, progesterone-mediated oocyte maturation, and chemical carcinogenesis. Conversely, hypermethylated-downregulated genes were found to be enriched in processes like epidermis development, keratinocyte differentiation, and skin development. Additionally, pathway analysis highlighted associations with estrogen signaling, Staphylococcus aureus infection, axon guidance, and arachidonic acid metabolism. Following the establishment of PPI networks and survival analysis, we identified 11 prognostic hub genes: CCNA2, CDC6, CDCA3, CKS2, DTL, HJURP, KRT5, KRT14, KRT15, KRT16, and NEK2. Notably, among the 11 hub genes, our findings indicate that CDC6 plays a pivotal role in enhancing the proliferation, migration, and invasion capabilities of melanoma cells in vitro. CONCLUSIONS: Our comprehensive genomic analyses reveal that genes with aberrant methylation exhibit differential expression during the transition from primary to metastatic melanoma. The identified genes, especially CDC6, which plays a crucial role in enhancing melanoma cell proliferation, migration, and invasion, provide valuable insights into potential methylation-based biomarkers. These findings could contribute significantly to advancing precision medicine in SKCM.

Glutamate acts on acid-sensing ion channels to worsen ischaemic brain injury.

Glutamate is traditionally viewed as the first messenger to activate NMDAR (N-methyl-D-aspartate receptor)-dependent cell death pathways in stroke1,2, but unsuccessful clinical trials with NMDAR antagonists implicate the engagement of other mechanisms3-7. Here we show that glutamate and its structural analogues, including NMDAR antagonist L-AP5 (also known as APV), robustly potentiate currents mediated by acid-sensing ion channels (ASICs) associated with acidosis-induced neurotoxicity in stroke4. Glutamate increases the affinity of ASICs for protons and their open probability, aggravating ischaemic neurotoxicity in both in vitro and in vivo models. Site-directed mutagenesis, structure-based modelling and functional assays reveal a bona fide glutamate-binding cavity in the extracellular domain of ASIC1a. Computational drug screening identified a small molecule, LK-2, that binds to this cavity and abolishes glutamate-dependent potentiation of ASIC currents but spares NMDARs. LK-2 reduces the infarct volume and improves sensorimotor recovery in a mouse model of ischaemic stroke, reminiscent of that seen in mice with Asic1a knockout or knockout of other cation channels4-7. We conclude that glutamate functions as a positive allosteric modulator for ASICs to exacerbate neurotoxicity, and preferential targeting of the glutamate-binding site on ASICs over that on NMDARs may be strategized for developing stroke therapeutics lacking the psychotic side effects of NMDAR antagonists.

Experimental study on the safety of photobiologic regulation therapy in the treatment of some non-epidermal tumors.

This study investigates the impact of Photobiomodulation (PBM) at different wavelengths on non-superficial cancer cells. Utilizing three laser protocols (650 nm, 810 nm, and 915 nm), the research explores cytotoxic effects, ROS generation, and cell migration. Results reveal varied responses across cell lines, with 810 nm PBM inducing significant ROS levels and inhibiting PAN-1 cell migration. The study suggests potential therapeutic applications for PBM in non-superficial cancers, emphasizing the need for further exploration in clinical settings.

The causal role between circulating immune cells and diabetic nephropathy: a bidirectional Mendelian randomization with mediating insights.

Diabetic nephropathy (DN) is a critical inflammatory condition linked to diabetes, affecting millions worldwide. This study employs Mendelian randomization (MR) to explore the causal relationship between immune cell signatures and DN, analyzing over 731 immune signatures and incorporating data from 1400 metabolites to investigate potential mediators. Despite no statistically significant influence of DN on immunophenotypes after FDR correction, some phenotypes with unadjusted low P-values warranted mention, including CD34 on Hematopoietic Stem Cell (Myeloid cell Panel), CD45 on CD33- HLA DR- (Myeloid cell Panel). Furthermore, three immunophenotypes were identified to have a significant impact on DN risk: CD16-CD56 on HLA DR+ NK (TBNK Panel), CD45 on HLA DR+ T cell (TBNK Panel), and CD33dim HLA DR+ CD11b+ AC (Myeloid cell Panel). Our findings underscore the critical role of immune cells in DN, highlighting potential mediators and offering new insights into its underlying mechanisms.