An Immunologic Mode of Multigenerational Transmission Governs a Gut Treg Setpoint.

At the species level, immunity depends on the selection and transmission of protective components of the immune system. A microbe-induced population of RORγ-expressing regulatory T cells (Tregs) is essential in controlling gut inflammation. We uncovered a non-genetic, non-epigenetic, non-microbial mode of transmission of their homeostatic setpoint. RORγ+ Treg proportions varied between inbred mouse strains, a trait transmitted by the mother during a tight age window after birth but stable for life, resistant to many microbial or cellular perturbations, then further transferred by females for multiple generations. RORγ+ Treg proportions negatively correlated with IgA production and coating of gut commensals, traits also subject to maternal transmission, in an immunoglobulin- and RORγ+ Treg-dependent manner. We propose a model based on a double-negative feedback loop, vertically transmitted via the entero-mammary axis. This immunologic mode of multi-generational transmission may provide adaptability and modulate the genetic tuning of gut immune responses and inflammatory disease susceptibility.

N-myristoyltransferase deficiency impairs activation of kinase AMPK and promotes synovial tissue inflammation.

N-myristoyltransferase (NMT) attaches the fatty acid myristate to the N-terminal glycine of proteins to sort them into soluble and membrane-bound fractions. Function of the energy-sensing AMP-activated protein kinase, AMPK, is myristoylation dependent. In rheumatoid arthritis (RA), pathogenic T cells shift glucose away from adenosine tri-phosphate production toward synthetic and proliferative programs, promoting proliferation, cytokine production, and tissue invasion. We found that RA T cells had a defect in NMT1 function, which prevented AMPK activation and enabled unopposed mTORC1 signaling. Lack of the myristate lipid tail disrupted the lysosomal translocation and activation of AMPK. Instead, myristoylation-incompetent RA T cells hyperactivated the mTORC1 pathway and differentiated into pro-inflammatory TH1 and TH17 helper T cells. In vivo, NMT1 loss caused robust synovial tissue inflammation, whereas forced NMT1 overexpression rescued AMPK activation and suppressed synovitis. Thus, NMT1 has tissue-protective functions by facilitating lysosomal recruitment of AMPK and dampening mTORC1 signaling.

Lunar eclipses illuminate timing and climate impact of medieval volcanism.

Explosive volcanism is a key contributor to climate variability on interannual to centennial timescales1. Understanding the far-field societal impacts of eruption-forced climatic changes requires firm event chronologies and reliable estimates of both the burden and altitude (that is, tropospheric versus stratospheric) of volcanic sulfate aerosol2,3. However, despite progress in ice-core dating, uncertainties remain in these key factors4. This particularly hinders investigation of the role of large, temporally clustered eruptions during the High Medieval Period (HMP, 1100-1300 CE), which have been implicated in the transition from the warm Medieval Climate Anomaly to the Little Ice Age5. Here we shed new light on explosive volcanism during the HMP, drawing on analysis of contemporary reports of total lunar eclipses, from which we derive a time series of stratospheric turbidity. By combining this new record with aerosol model simulations and tree-ring-based climate proxies, we refine the estimated dates of five notable eruptions and associate each with stratospheric aerosol veils. Five further eruptions, including one responsible for high sulfur deposition over Greenland circa 1182 CE, affected only the troposphere and had muted climatic consequences. Our findings offer support for further investigation of the decadal-scale to centennial-scale climate response to volcanic eruptions.

Beating the break-even point with a discrete-variable-encoded logical qubit.

Quantum error correction (QEC) aims to protect logical qubits from noises by using the redundancy of a large Hilbert space, which allows errors to be detected and corrected in real time1. In most QEC codes2-8, a logical qubit is encoded in some discrete variables, for example photon numbers, so that the encoded quantum information can be unambiguously extracted after processing. Over the past decade, repetitive QEC has been demonstrated with various discrete-variable-encoded scenarios9-17. However, extending the lifetimes of thus-encoded logical qubits beyond the best available physical qubit still remains elusive, which represents a break-even point for judging the practical usefulness of QEC. Here we demonstrate a QEC procedure in a circuit quantum electrodynamics architecture18, where the logical qubit is binomially encoded in photon-number states of a microwave cavity8, dispersively coupled to an auxiliary superconducting qubit. By applying a pulse featuring a tailored frequency comb to the auxiliary qubit, we can repetitively extract the error syndrome with high fidelity and perform error correction with feedback control accordingly, thereby exceeding the break-even point by about 16% lifetime enhancement. Our work illustrates the potential of hardware-efficient discrete-variable encodings for fault-tolerant quantum computation19.

Reconstruction of ancient microbial genomes from the human gut.

Loss of gut microbial diversity1-6 in industrial populations is associated with chronic diseases7, underscoring the importance of studying our ancestral gut microbiome. However, relatively little is known about the composition of pre-industrial gut microbiomes. Here we performed a large-scale de novo assembly of microbial genomes from palaeofaeces. From eight authenticated human palaeofaeces samples (1,000-2,000 years old) with well-preserved DNA from southwestern USA and Mexico, we reconstructed 498 medium- and high-quality microbial genomes. Among the 181 genomes with the strongest evidence of being ancient and of human gut origin, 39% represent previously undescribed species-level genome bins. Tip dating suggests an approximate diversification timeline for the key human symbiont Methanobrevibacter smithii. In comparison to 789 present-day human gut microbiome samples from eight countries, the palaeofaeces samples are more similar to non-industrialized than industrialized human gut microbiomes. Functional profiling of the palaeofaeces samples reveals a markedly lower abundance of antibiotic-resistance and mucin-degrading genes, as well as enrichment of mobile genetic elements relative to industrial gut microbiomes. This study facilitates the discovery and characterization of previously undescribed gut microorganisms from ancient microbiomes and the investigation of the evolutionary history of the human gut microbiota through genome reconstruction from palaeofaeces.

Programming hydrogel adhesion with engineered polymer network topology.

Hydrogel adhesion that can be easily modulated in magnitude, space, and time is desirable in many emerging applications ranging from tissue engineering and soft robotics to wearable devices. In synthetic materials, these complex adhesion behaviors are often achieved individually with mechanisms and apparatus that are difficult to integrate. Here, we report a universal strategy to embody multifaceted adhesion programmability in synthetic hydrogels. By designing the surface network topology of a hydrogel, supramolecular linkages that result in contrasting adhesion behaviors are formed on the hydrogel interface. The incorporation of different topological linkages leads to dynamically tunable adhesion with high-resolution spatial programmability without alteration of bulk mechanics and chemistry. Further, the association of linkages enables stable and tunable adhesion kinetics that can be tailored to suit different applications. We rationalize the physics of polymer chain slippage, rupture, and diffusion at play in the emergence of the programmable behaviors. With the understanding, we design and fabricate various soft devices such as smart wound patches, fluidic channels, drug-eluting devices, and reconfigurable soft robotics. Our study presents a simple and robust platform in which adhesion controllability in multiple aspects can be easily integrated into a single design of a hydrogel network.

METTL3 is essential for normal progesterone signaling during embryo implantation via m6A-mediated translation control of progesterone receptor.

Embryo implantation, a crucial step in human reproduction, is tightly controlled by estrogen and progesterone (P4) via estrogen receptor alpha and progesterone receptor (PGR), respectively. Here, we report that N6-methyladenosine (m6A), the most abundant mRNA modification in eukaryotes, plays an essential role in embryo implantation through the maintenance of P4 signaling. Conditional deletion of methyltransferase-like 3 (Mettl3), encoding the m6A writer METTL3, in the female reproductive tract using a Cre mouse line with Pgr promoter (Pgr-Cre) resulted in complete implantation failure due to pre-implantation embryo loss and defective uterine receptivity. Moreover, the uterus of Mettl3 null mice failed to respond to artificial decidualization. We further found that Mettl3 deletion was accompanied by a marked decrease in PGR protein expression. Mechanistically, we found that Pgr mRNA is a direct target for METTL3-mediated m6A modification. A luciferase assay revealed that the m6A modification in the 5' untranslated region (5'-UTR) of Pgr mRNA enhances PGR protein translation efficiency in a YTHDF1-dependent manner. Finally, we demonstrated that METTL3 is required for human endometrial stromal cell decidualization in vitro and that the METTL3-PGR axis is conserved between mice and humans. In summary, this study provides evidence that METTL3 is essential for normal P4 signaling during embryo implantation via m6A-mediated translation control of Pgr mRNA.

DrugAI: a multi-view deep learning model for predicting drug-target activating/inhibiting mechanisms.

Understanding the mechanisms of candidate drugs play an important role in drug discovery. The activating/inhibiting mechanisms between drugs and targets are major types of mechanisms of drugs. Owing to the complexity of drug-target (DT) mechanisms and data scarcity, modelling this problem based on deep learning methods to accurately predict DT activating/inhibiting mechanisms remains a considerable challenge. Here, by considering network pharmacology, we propose a multi-view deep learning model, DrugAI, which combines four modules, i.e. a graph neural network for drugs, a convolutional neural network for targets, a network embedding module for drugs and targets and a deep neural network for predicting activating/inhibiting mechanisms between drugs and targets. Computational experiments show that DrugAI performs better than state-of-the-art methods and has good robustness and generalization. To demonstrate the reliability of the predictive results of DrugAI, bioassay experiments are conducted to validate two drugs (notopterol and alpha-asarone) predicted to activate TRPV1. Moreover, external validation bears out 61 pairs of mechanism relationships between natural products and their targets predicted by DrugAI based on independent literatures and PubChem bioassays. DrugAI, for the first time, provides a powerful multi-view deep learning framework for robust prediction of DT activating/inhibiting mechanisms.

A DNA origami device spatially controls CD95 signalling to induce immune tolerance in rheumatoid arthritis.

DNA origami is capable of spatially organizing molecules into sophisticated geometric patterns with nanometric precision. Here we describe a reconfigurable, two-dimensional DNA origami with geometrically patterned CD95 ligands that regulates immune cell signalling to alleviate rheumatoid arthritis. In response to pH changes, the device reversibly transforms from a closed to an open configuration, displaying a hexagonal pattern of CD95 ligands with ~10 nm intermolecular spacing, precisely mirroring the spatial arrangement of CD95 receptor clusters on the surface of immune cells. In a collagen-induced arthritis mouse model, DNA origami elicits robust and selective activation of CD95 death-inducing signalling in activated immune cells located in inflamed synovial tissues. Such localized immune tolerance ameliorates joint damage with no noticeable side effects. This device allows for the precise spatial control of cellular signalling, expanding our understanding of ligand-receptor interactions and is a promising platform for the development of pharmacological interventions targeting these interactions.

Systematically assessing microbiome-disease associations identifies drivers of inconsistency in metagenomic research.

Evaluating the relationship between the human gut microbiome and disease requires computing reliable statistical associations. Here, using millions of different association modeling strategies, we evaluated the consistency-or robustness-of microbiome-based disease indicators for 6 prevalent and well-studied phenotypes (across 15 public cohorts and 2,343 individuals). We were able to discriminate between analytically robust versus nonrobust results. In many cases, different models yielded contradictory associations for the same taxon-disease pairing, some showing positive correlations and others negative. When querying a subset of 581 microbe-disease associations that have been previously reported in the literature, 1 out of 3 taxa demonstrated substantial inconsistency in association sign. Notably, >90% of published findings for type 1 diabetes (T1D) and type 2 diabetes (T2D) were particularly nonrobust in this regard. We additionally quantified how potential confounders-sequencing depth, glucose levels, cholesterol, and body mass index, for example-influenced associations, analyzing how these variables affect the ostensible correlation between Faecalibacterium prausnitzii abundance and a healthy gut. Overall, we propose our approach as a method to maximize confidence when prioritizing findings that emerge from microbiome association studies.

Total Synthesis of Penicibilaenes Enabled by a Tandem Double Conia-ene Type Reaction.

The total syntheses of penicibilaenes A and B are described. The key step is the tBuOK/DMSO-mediated tandem 5-exo-dig Conia-ene type reaction and 6-exo-dig Conia-ene type reaction to install the tricyclic [6.3.1.01,5] dodecane core of penicibilaenes from dibutynyl cyclohexanone in a single step, together with a sequence of copper-mediated conjugate addition and Crabtree's hydrogenation to forge the stereogenic centers at C5 and C2, respectively.

Advances in Flavonoid Research: Sources, Biological Activities, and Developmental Prospectives.

At present, the occurrence of a large number of infectious and non-communicable diseases poses a serious threat to human health as well as to drug development for the treatment of these diseases. One of the most significant challenges is finding new drug candidates that are therapeutically effective and have few or no side effects. In this respect, the active compounds in medicinal plants, especially flavonoids, are potentially useful compounds with a wide range of pharmacological activities. They are naturally present in nature and valuable in the treatment of many infectious and non-communicable diseases. Flavonoids are divided into fourteen categories and are mainly derived from plant extraction, chemical synthesis and structural modification, and biosynthesis. The structural modification of flavonoids is an important way to discover new drugs, but biosynthesis is currently considered the most promising research direction with the potential to revolutionize the new production pipeline in the synthesis of flavonoids. However, relevant problems such as metabolic pathway analyses and cell synthesis protocols for flavonoids need to be addressed on an urgent basis. In the present review, new research techniques for assessing the biological activities of flavonoids and the mechanisms of their biological activities are elucidated and their modes of interaction with other drugs are described. Moreover, novel drug delivery systems, such as nanoparticles, bioparticles, colloidals, etc., are gradually becoming new means of addressing the issues of poor hydrophilicity, lipophilicity, poor chemical stability, and low bioavailability of flavonoids. The present review summarizes the latest research progress on flavonoids, existing problems with their therapeutic efficacy, and how these issues can be solved with the research on flavonoids.

Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL.

PURPOSE: The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort. METHODS: This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort. RESULTS: In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed. CONCLUSION: PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

Neuropilin-1 is a novel host factor modulating the entry of hepatitis B virus.

BACKGROUND & AIMS: Sodium taurocholate cotransporting polypeptide (NTCP) has been identified as the cellular receptor for hepatitis B virus (HBV). However, hepatocytes expressing NTCP exhibit varying susceptibilities to HBV infection. This study aimed to investigate whether other host factors modulate the process of HBV infection. METHODS: Liver biopsy samples obtained from children with hepatitis B were used for single-cell sequencing and susceptibility analysis. Primary human hepatocytes, HepG2-NTCP cells, and human liver chimeric mice were used to analyze the effect of candidate host factors on HBV infection. RESULTS: Single-cell sequencing and susceptibility analysis revealed a positive correlation between neuropilin-1 (NRP1) expression and HBV infection. In the HBV-infected cell model, NRP1 overexpression before HBV inoculation significantly enhanced viral attachment and internalization, and promoted viral infection in the presence of NTCP. Mechanistic studies indicated that NRP1 formed a complex with LHBs and NTCP. The NRP1 b domain mediated its interaction with conserved arginine residues at positions 88 and 92 in the preS1 domain of the HBV envelope protein LHBs. This NRP1-preS1 interaction subsequently promoted the binding of preS1 to NTCP, facilitating viral infection. Moreover, disruption of the NRP1-preS1 interaction by the NRP1 antagonist EG00229 significantly attenuated the binding affinity between NTCP and preS1, thereby inhibiting HBV infection both in vitro and in vivo. CONCLUSIONS: Our findings indicate that NRP1 is a novel host factor for HBV infection, which interacts with preS1 and NTCP to modulate HBV entry into hepatocytes. IMPACT AND IMPLICATIONS: HBV infection is a global public health problem, but the understanding of the early infection process of HBV remains limited. Through single-cell sequencing, we identified a novel host factor, NRP1, which modulates HBV entry by interacting with HBV preS1 and NTCP. Moreover, antagonists targeting NRP1 can inhibit HBV infection both in vitro and in vivo. This study could further advance our comprehension of the early infection process of HBV.

Miro-mediated mitochondrial transport: A new dimension for disease-related abnormal cell metabolism?

Mitochondria are versatile and highly dynamic organelles found in eukaryotic cells that play important roles in a variety of cellular processes. The importance of mitochondrial transport in cell metabolism, including variations in mitochondrial distribution within cells and intercellular transfer, has grown in recent years. Several studies have demonstrated that abnormal mitochondrial transport represents an early pathogenic alteration in a variety of illnesses, emphasizing its significance in disease development and progression. Mitochondrial Rho GTPase (Miro) is a protein found on the outer mitochondrial membrane that is required for cytoskeleton-dependent mitochondrial transport, mitochondrial dynamics (fusion and fission), and mitochondrial Ca2+ homeostasis. Miro, as a critical regulator of mitochondrial transport, has yet to be thoroughly investigated in illness. This review focuses on recent developments in recognizing Miro as a crucial molecule in controlling mitochondrial transport and investigates its roles in diverse illnesses. It also intends to shed light on the possibilities of targeting Miro as a therapeutic method for a variety of diseases.

Regulatory role of RGMb in lung injury promoted by the combination of carbon ion irradiation and anti-PD-1 antibody through Erk1/2 and p38 MAPK pathways.

The combination of carbon ion radiotherapy and anti-PD-1 antibody represents a new approach to treating thoracic tumors. However, the lung damage caused by this combination therapy may limit its use, and the potential mechanisms for this are worthy of investigation. The objective of this research was to examine the potential involvement of repulsive guidance molecule b (RGMb) in lung damage promoted by the utilization of carbon ion irradiation combined with an anti-PD-1 antibody. The C57BL/6 mice have been randomly separated into four distinct groups: control, anti-PD-1, whole thorax carbon ion irradiation, and irradiation in combination with anti-PD-1 treatment groups (combination group). Detection of pathological changes in lung tissue using HE staining. Detection of pulmonary fibrosis by Masson staining and the hydroxyproline assay. ELISA to detect TNF-α, TGF-ß, IL-6, and IL-1ß expression levels within lung homogenates. The expression of RGMb, p38 MAPK, and Erk1/2 pathways was detected using a fully automated digital Western blotting system WES (ProteinSimple, USA). Flow cytometry was employed to analyze tissue-resident memory T cells (TRM) within the lung. Subsequently, the siRNA gene was employed to induce the downregulation of RGMb in mice in order to validate the involvement of RGMb in radiation-immune lung injury. The present study observed a significant increase in both inflammatory and fibrotic indicators within the mice group's lung tissue that received the combination treatment. The combination group exhibited elevated levels of TGF-ß, TNF-α, IL-6, and IL-1ß in lung homogenates. Anti-PD-1 antibody and carbon ion irradiation, upregulated RGMb, phospho-p38 MAPK and phospho-Erk1/2. The results obtained from the flow cytometry analysis indicated that the combination group was significantly higher in the number of clonal expansion TRMs, which were predominantly characterized by the expression of CD8+CD103+CD69-TRMs. The downregulate of RGMb via siRNA in mice resulted in a decrease in phospho-p38 MAPK and phospho-Erk1/2. The combination group exhibited a reduction in TNF-α, TGF-ß, IL-6, and IL-1ß in their lung tissues, and the number of CD8+CD103+CD69-TRM was significantly reduced. The combination group exhibited a significant improvement in inflammatory and fibrotic indicators within the lung tissues. Anti-PD-1 antibody and carbon ion irradiation synergistically regulate RGMb, leading to strong clonal expansion of lung TRM through the p38 MAPK and Erk1/2 pathways. The present study offers valuable insights into the treatment of lung injury due to the combined administration of carbon ion radiotherapy and anti-PD-1 antibody therapy.

Engineering Sonosensitizer-Derived Nanotheranostics for Augmented Sonodynamic Therapy.

Sonodynamic therapy (SDT), featuring noninvasive, deeper penetration, low cost, and repeatability, is a promising therapy approach for deep-seated tumors. However, the general or only utilization of SDT shows low efficiency and unsatisfactory treatment outcomes due to the complicated tumor microenvironment (TME) and SDT process. To circumvent the issues, three feasible approaches for enhancing SDT-based therapeutic effects, including sonosensitizer optimization, strategies for conquering hypoxia TME, and combinational therapy are summarized, with a particular focus on the combination therapy of SDT with other therapy modalities, including chemodynamic therapy, photodynamic therapy, photothermal therapy, chemotherapy, starvation therapy, gas therapy, and immunotherapy. In the end, the current challenges in SDT-based therapy on tumors are discussed and feasible approaches for enhanced therapeutic effects are provided. It is envisioned that this review will provide new insight into the strategic design of high-efficiency sonosensitizer-derived nanotheranostics, thereby augmenting SDT and accelerating the potential clinical transformation.

AFSE: towards improving model generalization of deep graph learning of ligand bioactivities targeting GPCR proteins.

Ligand molecules naturally constitute a graph structure. Recently, many excellent deep graph learning (DGL) methods have been proposed and used to model ligand bioactivities, which is critical for the virtual screening of drug hits from compound databases in interest. However, pharmacists can find that these well-trained DGL models usually are hard to achieve satisfying performance in real scenarios for virtual screening of drug candidates. The main challenges involve that the datasets for training models were small-sized and biased, and the inner active cliff cases would worsen model performance. These challenges would cause predictors to overfit the training data and have poor generalization in real virtual screening scenarios. Thus, we proposed a novel algorithm named adversarial feature subspace enhancement (AFSE). AFSE dynamically generates abundant representations in new feature subspace via bi-directional adversarial learning, and then minimizes the maximum loss of molecular divergence and bioactivity to ensure local smoothness of model outputs and significantly enhance the generalization of DGL models in predicting ligand bioactivities. Benchmark tests were implemented on seven state-of-the-art open-source DGL models with the potential of modeling ligand bioactivities, and precisely evaluated by multiple criteria. The results indicate that, on almost all 33 GPCRs datasets and seven DGL models, AFSE greatly improved their enhancement factor (top-10%, 20% and 30%), which is the most important evaluation in virtual screening of hits from compound databases, while ensuring the superior performance on RMSE and $r^2$. The web server of AFSE is freely available at http://noveldelta.com/AFSE for academic purposes.

Identifying the kind behind SMILES-anatomical therapeutic chemical classification using structure-only representations.

Anatomical Therapeutic Chemical (ATC) classification for compounds/drugs plays an important role in drug development and basic research. However, previous methods depend on interactions extracted from STITCH dataset which may make it depend on lab experiments. We present a pilot study to explore the possibility of conducting the ATC prediction solely based on the molecular structures. The motivation is to eliminate the reliance on the costly lab experiments so that the characteristics of a drug can be pre-assessed for better decision-making and effort-saving before the actual development. To this end, we construct a new benchmark consisting of 4545 compounds which is with larger scale than the one used in previous study. A light-weight prediction model is proposed. The model is with better explainability in the sense that it is consists of a straightforward tokenization that extracts and embeds statistically and physicochemically meaningful tokens, and a deep network backed by a set of pyramid kernels to capture multi-resolution chemical structural characteristics. Its efficacy has been validated in the experiments where it outperforms the state-of-the-art methods by 15.53% in accuracy and by 69.66% in terms of efficiency. We make the benchmark dataset, source code and web server open to ease the reproduction of this study.

CircACTR2 attenuated the effects of tetramethylpyrazine on human kidney cell injury.

Tetramethylpyrazine (TMP) is one of the active ingredients of Chuan Xiong that has been reported to have effects on numerous diseases, including diabetic nephropathy (DN). Whereas, related molecular mechanisms are not fully elucidated. We aimed to explore circACTR2's role in TMP-mediated protective effects on DN. In vitro DN condition was established in human kidney cells (HK-2) by treating high glucose (HG). CCK-8 assay and flow cytometry assay were used to observe cell viability and survival. Oxidative stress was determined by the associated markers using kits. The release of inflammatory factors was detected using ELISA kits. Quantitative real-time PCR (qPCR) and western blot were utilized for expression analysis of cricACTR2, miR-140-5p, and GLI pathogenesis-related 2 (GLIPR2). The binding between miR-140-5p and circACTR2 or GLIPR2 was confirmed by dual-luciferase, RIP, and pull-down studies. HG largely induced HK-2 cell apoptosis, oxidative stress, and inflammation, which were alleviated by TMP. CircACTR2's expression was enhanced in HG-treated HK-2 cells but attenuated in HG + TMP-treated HK-2 cells. CircACTR2 overexpression attenuated the functional effects of TMP and thus restored HG-induced cell apoptosis, oxidative stress, and inflammation. CircACTR2 bound to miR-140-5p to enhance the expression of GLIPR2. MiR-140-5p restoration or GLIPR2 inhibition reversed the role of circACTR2 overexpression. CircACTR2 attenuated the protective effects of TMP on HG-induced HK-2 cell damages by regulating the miR-140-5p/GLIPR2 network, indicating that circACTR2 was involved in the functional network of TMP in DN.