HiChIP-based Epigenomic Footprinting Identifies a Promoter Variant of UXS1 that Confers Genetic Susceptibility to Gastroesophageal Cancer.

Genome-wide association studies (GWAS) have identified more than a hundred single nucleotide variants (SNVs) associated with the risk of gastroesophageal cancer (GEC). The majority of the identified SNVs map to noncoding regions of the genome. Uncovering the causal SNVs and the genes they modulate could help improve GEC prevention and treatment. Here, we used HiChIP against histone 3 lysine 27 acetylation (H3K27ac) to simultaneously annotate active promoters and enhancers, identify the interactions between them, and detect nucleosome free regions (NFRs) harboring potential causal SNVs in a single assay. Application of H3K27Ac HiChIP in GEC relevant models identified 61 potential functional SNVs that reside in NFRs and interact with 49 genes at 17 loci. The approach led to a 67% reduction in the number of SNVs in linkage disequilibrium at these 17 loci, and at seven loci a single putative causal SNV was identified. One SNV, rs147518036, located within the promoter of the UDP-glucuronate decarboxylase 1 (UXS1) gene appeared to underlie the GEC risk association captured by the rs75460256 index SNV. The rs147518036 SNV creates a GABPA DNA recognition motif, resulting in increased promoter activity, and CRISPR-mediated inhibition of the UXS1 promoter reduced viability of GEC cells. These findings provide a framework that simplifies the identification of potentially functional regulatory SNVs and target genes underlying risk-associated loci. In addition, the study implicates increased expression of the enzyme UXS1 and activation of its metabolic pathway as a predisposition to gastric cancer, which highlights potential therapeutic avenues to treat this disease.

Mapping annual 10-m soybean cropland with spatiotemporal sample migration.

China, as the world's biggest soybean importer and fourth-largest producer, needs accurate mapping of its planting areas for global food supply stability. The challenge lies in gathering and collating ground survey data for different crops. We proposed a spatiotemporal migration method leveraging vegetation indices' temporal characteristics. This method uses a feature space of six integrals from the crops' phenological curves and a concavity-convexity index to distinguish soybean and non-soybean samples in cropland. Using a limited number of actual samples and our method, we extracted features from optical time-series images throughout the soybean growing season. The cloud and rain-affected data were supplemented with SAR data. We then used the random forest algorithm for classification. Consequently, we developed the 10-meter resolution ChinaSoybean10 maps for the ten primary soybean-producing provinces from 2019 to 2022. The map showed an overall accuracy of about 93%, aligning significantly with the statistical yearbook data, confirming its reliability. This research aids soybean growth monitoring, yield estimation, strategy development, resource management, and food scarcity mitigation, and promotes sustainable agriculture.

Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models.

BACKGROUND: Influenza is a highly contagious respiratory disease that presents a significant challenge to public health globally. Therefore, effective influenza prediction and prevention are crucial for the timely allocation of resources, the development of vaccine strategies, and the implementation of targeted public health interventions. METHOD: In this study, we utilized historical influenza case data from January 2013 to December 2021 in Fuzhou to develop four regression prediction models: SARIMA, Prophet, Holt-Winters, and XGBoost models. Their predicted performance was assessed by using influenza data from the period from January 2022 to December 2022 in Fuzhou. These models were used for fitting and prediction analysis. The evaluation metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), were employed to compare the performance of these models. RESULTS: The results indicate that the epidemic of influenza in Fuzhou exhibits a distinct seasonal and cyclical pattern. The influenza cases data displayed a noticeable upward trend and significant fluctuations. In our study, we employed SARIMA, Prophet, Holt-Winters, and XGBoost models to predict influenza outbreaks in Fuzhou. Among these models, the XGBoost model demonstrated the best performance on both the training and test sets, yielding the lowest values for MSE, RMSE, and MAE among the four models. CONCLUSION: The utilization of the XGBoost model significantly enhances the prediction accuracy of influenza in Fuzhou. This study makes a valuable contribution to the field of influenza prediction and provides substantial support for future influenza response efforts.

Theranostic antibacterial hydrogel based on biopolymers cross-linked and doped with phytic acid from rice bran for wound healing.

Theranostic antibacterial wound dressing is highly recommended in practical applications. The conventional methods of integrating diagnostic and therapeutic functions have the disadvantages of complicated preparation, mutual interference, inability to effectively broad spectrum antibacterial property, and easy to induce drug-resistant bacteria. Herein, a pH and light-responsive theranostic antibacterial hydrogel is developed by biopolymers polyvinyl alcohol (PVA) and polyaniline (PANI), and cross-linking with phytic acid (PA), which is widely present in rice bran. The biological polymer-based conductive hydrogel enables timely diagnosis and photothermal sterilization in-situ for wound healing. Because PANI is highly sensitive to pH changes in the bacterial microenvironment, the hydrogel can detect bacterial infections at concentrations as low as 103 CFU/mL. Subsequently, PANI absorbs near-infrared light to achieve on-demand exothermic sterilization (under 808 nm irradiation for 20 min, the killing ratios for Staphylococcus aureus and Escherichia coli reached almost 100 %). In addition, the hydrogel can monitor the intensity of joint movement to avoid wound re-tearing sensitively. In vitro cytotoxicity and hemocompatibility experiments and in vivo full-thickness infected wound model indicate that the hydrogel has good biocompatibility, antibacterial ability, and can accelerate the wound healing effectively. This work will promote the development of wearable electronic devices and precision medicine.

Cis-regulatory control of transcriptional timing and noise in response to estrogen.

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single-cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We found that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Causal association between air pollution and autoimmune diseases: a two-sample Mendelian randomization study.

Background: In recent years, an increasing number of observational studies have reported the impact of air pollution on autoimmune diseases (ADs). However, no Mendelian randomization (MR) studies have been conducted to investigate the causal relationships. To enhance our understanding of causality, we examined the causal relationships between particulate matter (PM) and nitrogen oxides (NOx) and ADs. Methods: We utilized genome-wide association study (GWAS) data on PM and NOx from the UK Biobank in European and East Asian populations. We also extracted integrated GWAS data from the Finnish consortium and the Japanese Biobank for two-sample MR analysis. We employed inverse variance weighted (IVW) analysis to assess the causal relationship between PM and NOx exposure and ADs. Additionally, we conducted supplementary analyses using four methods, including IVW (fixed effects), weighted median, weighted mode, and simple mode, to further investigate this relationship. Results: In the European population, the results of MR analysis suggested a statistically significant association between PM2.5 and psoriasis only (OR = 3.86; 95% CI: 1.89-7.88; PIVW < 0.00625), while a potential association exists between PM2.5-10 and vitiligo (OR = 7.42; 95% CI: 1.02-53.94; PIVW < 0.05), as well as between PM2.5 and systemic lupus erythematosus (OR = 68.17; 95% CI: 2.17-2.1e+03; PIVW < 0.05). In East Asian populations, no causal relationship was found between air pollutants and the risk of systemic lupus erythematosus and rheumatoid arthritis (PIVW > 0.025). There was no pleiotropy in the results. Conclusion: Our results suggest a causal association between PM2.5 and psoriasis in European populations. With the help of air pollution prevention and control, the harmful progression of psoriasis may be slowed.

Integrating machine learning and nontargeted plasma lipidomics to explore lipid characteristics of premetabolic syndrome and metabolic syndrome.

Objective: To identify plasma lipid characteristics associated with premetabolic syndrome (pre-MetS) and metabolic syndrome (MetS) and provide biomarkers through machine learning methods. Methods: Plasma lipidomics profiling was conducted using samples from healthy individuals, pre-MetS patients, and MetS patients. Orthogonal partial least squares-discriminant analysis (OPLS-DA) models were employed to identify dysregulated lipids in the comparative groups. Biomarkers were selected using support vector machine recursive feature elimination (SVM-RFE), random forest (rf), and least absolute shrinkage and selection operator (LASSO) regression, and the performance of two biomarker panels was compared across five machine learning models. Results: In the OPLS-DA models, 50 and 89 lipid metabolites were associated with pre-MetS and MetS patients, respectively. Further machine learning identified two sets of plasma metabolites composed of PS(38:3), DG(16:0/18:1), and TG(16:0/14:1/22:6), TG(16:0/18:2/20:4), and TG(14:0/18:2/18:3), which were used as biomarkers for the pre-MetS and MetS discrimination models in this study. Conclusion: In the initial lipidomics analysis of pre-MetS and MetS, we identified relevant lipid features primarily linked to insulin resistance in key biochemical pathways. Biomarker panels composed of lipidomics components can reflect metabolic changes across different stages of MetS, offering valuable insights for the differential diagnosis of pre-MetS and MetS.

BnAP2-12 overexpression delays ramie flowering: evidence from AP2/ERF gene expression.

Introduction: The APETALA2/ethylene response factor (AP2/ERF) superfamily plays a significant role in regulating plant gene expression in response to growth and development. To date, there have been no studies into whether the ramie AP2/ERF genes are involved in the regulation of flower development. Methods: Here, 84 BnAP2/ERF members were identified from the ramie genome database, and various bioinformatics data on the AP2/ERF gene family, structure, replication, promoters and regulatory networks were analysed. BnAP2-12 was transferred into Arabidopsis through the flower-dipping method. Results: Phylogenetic analysis classified the 84 BnAP2/ERF members into four subfamilies: AP2 (18), RAV (3), ERF (42), and DREB (21). The functional domain analysis of genes revealed 10 conserved motifs. Genetic mapping localised the 84 members on 14 chromosomes, among which chromosomes 1, 3, 5, and 8 had more members. Collinearity analysis revealed that 43.37% possibly resulted from replication events during the evolution of the ramie genome. Promoter sequence analysis identified classified cis-acting elements associated with plant growth and development, and responses to stress, hormones, and light. Transcriptomic comparison identified 3,635 differentially expressed genes (DEGs) between male and female flowers (1,803 and 1,832 upregulated and downregulated genes, respectively). Kyoto Encyclopaedia of Genes and Genomes pathway analysis categorised DEGs involved in metabolic pathways and biosynthesis of secondary metabolites. Gene Ontology enrichment analysis further identified enriched genes associated with pollen and female gamete formations. Of the 84 BnAP2/ERFs genes, 22 and 8 upregulated and downregulated genes, respectively, were present in female flowers. Co-expression network analysis identified AP2/ERF members associated with flower development, including BnAP2-12. Subcellular localisation analysis showed that the BnAP2-12 protein is localised in the nucleus and cell membrane. Overexpression BnAP2-12 delayed the flowering time of Arabidopsis thaliana. Conclusion: These findings provide insights into the mechanism of ramie flower development.

Complete biodegradation of tetrabromobisphenol A through sequential anaerobic reductive dehalogenation and aerobic oxidation.

Tetrabromobisphenol A (TBBPA), a common brominated flame retardant and a notorious pollutant in anaerobic environments, resists aerobic degradation but can undergo reductive dehalogenation to produce bisphenol A (BPA), an endocrine disruptor. Conversely, BPA is resistant to anaerobic biodegradation but susceptible to aerobic degradation. Microbial degradation of TBBPA via anoxic/oxic processes is scarcely documented. We established an anaerobic microcosm for TBBPA dehalogenation to BPA facilitated by humin. Dehalobacter species increased with a growth yield of 1.5 × 108 cells per µmol Br- released, suggesting their role in TBBPA dehalogenation. We innovatively achieved complete and sustainable biodegradation of TBBPA in sand/soil columns columns, synergizing TBBPA reductive dehalogenation by anaerobic functional microbiota and BPA aerobic oxidation by Sphingomonas sp. strain TTNP3. Over 42 days, 95.11 % of the injected TBBPA in three batches was debrominated to BPA. Following injection of strain TTNP3 cells, 85.57 % of BPA was aerobically degraded. Aerobic BPA degradation column experiments also indicated that aeration and cell colonization significantly increased degradation rates. This treatment strategy provides valuable technical insights for complete TBBPA biodegradation and analogous contaminants.

[Characterization of Reductive Dechlorination of Chlorinated Ethylenes by Anaerobic Consortium].

Tetrachloroethylene （PCE） and trichloroethylene （TCE） are typical volatile halogenated organic compounds in groundwater that pose serious threats to the ecological environment and human health. To obtain an anaerobic microbial consortium capable of efficiently dechlorinating PCE and TCE to a non-toxic end product and to explore its potential in treating contaminated groundwater， an anaerobic microbial consortium W-1 that completely dechlorinated PCE and TCE to ethylene was obtained by repeatedly feeding PCE or TCE into the contaminated groundwater collected from an industrial site. The dechlorination rates of PCE and TCE were （120.1 ±4.9） µmol·ï¼ˆL·d）-1 and （172.4 ±21.8） µmol·ï¼ˆL·d）-1 in W-1， respectively. 16S rRNA gene amplicon sequencing and quantitative PCR （qPCR） showed that the relative abundance of Dehalobacter increased from 1.9% to 57.1%， with the gene copy number increasing by 1.7×107 copies per 1 µmol Cl- released when 98.3 µmol of PCE was dechlorinated to cis-1，2-dichloroethylene （cis-1，2-DCE）. The relative abundance of Dehalococcoides increased from 1.1% to 53.8% when cis-1，2-DCE was reductively dechlorinated to ethylene. The growth yield of Dehalococcoides gene copy number increased by 1.7×108 copies per 1 µmol Cl- released for the complete reductive dechlorination of PCE to ethylene. The results indicated that Dehalobacter and Dehalococcoides cooperated to completely detoxify PCE. When TCE was used as the only electron acceptor， the relative abundance of Dehalococcoides increased from （29.1 ±2.4）% to （7.7 ±0.2）%， and gene copy number increased by （1.9 ±0.4）×108 copies per 1 µmol Cl- released， after dechlorinating 222.8 µmol of TCE to ethylene. The 16S rRNA gene sequence of Dehalococcoides LWT1， the main functional dehalogenating bacterium in enrichment culture W-1， was obtained using PCR and Sanger sequencing， and it showed 100% similarity with the 16S rRNA gene sequence of D. mccartyi strain 195. The anaerobic microbial consortium W-1 was also bioaugmented into the groundwater contaminated by TCE at a concentration of 418.7 µmol·L-1. The results showed that （69.2 ±9.8）% of TCE could be completely detoxified to ethylene within 28 days with a dechlorination rate of （10.3 ±1.5） µmol·ï¼ˆL·d）-1. This study can provide the microbial resource and theoretical guidance for the anaerobic microbial remediation in PCE or TCE-contaminated groundwater.

Evaluating the risk of developing hyperuricemia in patients with type 2 diabetes mellitus using least absolute shrinkage and selection operator regression and machine learning algorithm.

Background: Hyperuricemia is a common complication of type 2 diabetes mellitus and can lead to serious consequences such as gout and kidney disease. Methods: Patients with type 2 diabetes mellitus from six different communities in Fuzhou were recruited from June to December 2022. Questionnaires, physical examinations, and laboratory tests were conducted to collect data on various variables. Variable screening steps were performed using univariate and multivariate stepwise regression, least absolute shrinkage and selection operator (LASSO) regression, and Boruta feature selection. The dataset was divided into a training-testing set (80%) and an independent validation set (20%). Six machine learning models were built and validated. Results: A total of 8243 patients with type 2 diabetes mellitus were included in this study. According to Occam's razor method, the LASSO regression algorithm was determined to be the optimal risk factors selection method, and nine variables were identified as parameters for the risk assessment model. The absence of diabetes medication and elevated fasting blood glucose levels exhibited a negative correlation with the risk of hyperuricemia. Conversely, seven other variables demonstrated a positive association with the risk of hyperuricemia among patients diagnosed with type 2 diabetes mellitus. Among the six machine learning models, the artificial neural network (ANN) model demonstrated the highest performance. It achieved an areas under curve of 0.736, accuracy of 68.3%, sensitivity of 65.0%, specificity of 72.2%, precision of 73.6% and F1-score of 69.0%. Conclusions: We developed an ANN model to better evaluate the risk of hyperuricemia in the type 2 diabetes population. In the type 2 diabetes population, women should pay particular attention to their uric acid levels, and type 2 diabetics should not neglect their obesity level, blood pressure, kidney function and lipid profile during their regular medical check-ups, in order to do their best to avoid the risks associated with the combination of type 2 diabetes and hyperuricemia.

WTAP regulates the production of reactive oxygen species, promotes malignant progression, and is closely related to the tumor microenvironment in glioblastoma.

RNA modifications have been substantiated to regulate the majority of physiological activities in the organism, including the metabolism of reactive oxygen species (ROS), which plays an important role in cells. As for the effect of RNA modification genes on ROS metabolism in glioblastoma (GBM), it has not been studied yet. Therefore, this study aims to screen the RNA modification genes that are most related to ROS metabolism and explore their effects on the biological behavior of GBM in vitro. Here, an association between WTAP and ROS metabolism was identified by bioinformatics analysis, and WTAP was highly expressed in GBM tissue compared with normal brain tissue, which was confirmed by western blotting and immunohistochemical staining. When using a ROS inducer to stimulate GBM cells in the WTAP overexpression group, the ROS level increased more significantly and the expression levels of superoxide dismutase 1 (SOD1) and catalase (CAT) also increased. Next, colony formation assay, wound healing assay, and transwell assay were performed to investigate the proliferation, migration, and invasion of GBM cells. The results showed that WTAP, as an oncogene, promoted the malignant progression of GBM cells. Functional enrichment analysis predicted that WTAP was involved in the regulation of tumor/immune-related functional pathways. Western blotting was used to identify that WTAP had a regulatory effect on the phosphorylation of PI3K/Akt signaling. Finally, based on functional enrichment analysis, we further performed immune-related analysis on WTAP. In conclusion, this study analyzed WTAP from three aspects, which provided new ideas for the treatment of GBM.

ASPSCR1-TFE3 reprograms transcription by organizing enhancer loops around hexameric VCP/p97.

The t(X,17) chromosomal translocation, generating the ASPSCR1::TFE3 fusion oncoprotein, is the singular genetic driver of alveolar soft part sarcoma (ASPS) and some Xp11-rearranged renal cell carcinomas (RCCs), frustrating efforts to identify therapeutic targets for these rare cancers. Here, proteomic analysis identifies VCP/p97, an AAA+ ATPase with known segregase function, as strongly enriched in co-immunoprecipitated nuclear complexes with ASPSCR1::TFE3. We demonstrate that VCP is a likely obligate co-factor of ASPSCR1::TFE3, one of the only such fusion oncoprotein co-factors identified in cancer biology. Specifically, VCP co-distributes with ASPSCR1::TFE3 across chromatin in association with enhancers genome-wide. VCP presence, its hexameric assembly, and its enzymatic function orchestrate the oncogenic transcriptional signature of ASPSCR1::TFE3, by facilitating assembly of higher-order chromatin conformation structures demonstrated by HiChIP. Finally, ASPSCR1::TFE3 and VCP demonstrate co-dependence for cancer cell proliferation and tumorigenesis in vitro and in ASPS and RCC mouse models, underscoring VCP's potential as a novel therapeutic target.

Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model.

Air pollution has become a significant concern for human health, and its impact on influenza, has been increasingly recognized. This study aims to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza and to confirm a better method for infectious disease surveillance. Spearman correlation coefficient was used to evaluate the correlation between air pollution and the influenza case counts. VIF was used to test for collinearity among selected air pollutants. OLS regression, GWR, and STWR models were fitted to explore the potential spatiotemporal relationship between air pollution and influenza. The R2, the RSS and the AICc were used to evaluate and compare the models. In addition, the DTW and K-medoids algorithms were applied to cluster the county-level time-series coefficients. Compared with the OLS regression and GWR models, STWR model exhibits superior fit especially when the influenza outbreak changes rapidly and is able to more accurately capture the changes in different regions and time periods. We discovered that identical air pollutant factors may yield contrasting impacts on influenza within the same period in different areas of Fuzhou. NO2 and PM10 showed opposite impacts on influenza in the eastern and western areas of Fuzhou during all periods. Additionally, our investigation revealed that the relationship between air pollutant factors and influenza may exhibit temporal variations in certain regions. From 2013 to 2019, the influence coefficient of O3 on influenza epidemic intensity changed from negative to positive in the western region and from positive to negative in the eastern region. STWR model could be a useful method to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza in geospatial processes. The research findings emphasize the importance of considering spatiotemporal heterogeneity when studying the relationship between air pollution and influenza.

Low temperature synthesis of chiral carbon dots for reducing H2O2 damage.

Recently, researches focused towards the chiral nanostructures have attracted vast attention. However, the synthesis of chiral carbon dots (CDs) through one-step method is still rather scarce. Herein, a universal approach to green synthesis of chiral CDs at low temperature was proposed. In brief, L-FruCDs and D-FruCDs were obtained by only heating the fructose and chiral cysteine molecules in the sodium hydroxide aqueous solution under atmospheric pressure. Circular dichroism spectra show that these prepared CDs exhibit opposite chirality ranging from 210 to 260 nm. Specially, the prepared L-FruCDs could reduce the intracellular oxidative damage induced by hydrogen peroxide and display a superior performance than that of D-FruCDs. Mechanism studies indicate that the probably protect mechanism is ascribed to the directly consumption the intracellular ROS. And the clearance efficiency of intracellular reactive oxygen species of L-FruCDs is 3-times than that of D-FruCDs. Furthermore, this newly synthesized method is scalable by replacing fructose precursor with ascorbic acid, sucrose or lactose. In sum, our work provides a new method for the preparation of chiral CDs and achieve a great success in exploring the chiral biological effects at nanoscale.

Neuropeptides and Their Roles in the Cerebellum.

Although more than 30 different types of neuropeptides have been identified in various cell types and circuits of the cerebellum, their unique functions in the cerebellum remain poorly understood. Given the nature of their diffuse distribution, peptidergic systems are generally assumed to exert a modulatory effect on the cerebellum via adaptively tuning neuronal excitability, synaptic transmission, and synaptic plasticity within cerebellar circuits. Moreover, cerebellar neuropeptides have also been revealed to be involved in the neurogenetic and developmental regulation of the developing cerebellum, including survival, migration, differentiation, and maturation of the Purkinje cells and granule cells in the cerebellar cortex. On the other hand, cerebellar neuropeptides hold a critical position in the pathophysiology and pathogenesis of many cerebellar-related motor and psychiatric disorders, such as cerebellar ataxias and autism. Over the past two decades, a growing body of evidence has indicated neuropeptides as potential therapeutic targets to ameliorate these diseases effectively. Therefore, this review focuses on eight cerebellar neuropeptides that have attracted more attention in recent years and have significant potential for clinical application associated with neurodegenerative and/or neuropsychiatric disorders, including brain-derived neurotrophic factor, corticotropin-releasing factor, angiotensin II, neuropeptide Y, orexin, thyrotropin-releasing hormone, oxytocin, and secretin, which may provide novel insights and a framework for our understanding of cerebellar-related disorders and have implications for novel treatments targeting neuropeptide systems.

Pretargeted radiotherapy and synergistic treatment of metastatic, castration-resistant prostate cancer using cross-linked, PSMA-targeted lipoic acid nanoparticles.

Metastatic castration-resistant prostate cancer (CRPC) is a currently incurable disease associated with high mortality. Novel therapeutic approaches for CRPC are urgently needed to improve prognosis. In this study, we developed cross-linked, PSMA-targeted lipoic acid nanoparticles (cPLANPs), which can interact with transmembrane glycoprotein to accumulate inside prostate cancer cells, where they upregulate caspase-3, downregulate anti-apoptotic B-cell lymphoma-2 (BCL-2), and thereby induce apoptosis. The trans-cyclooctene (TCO) decoration on cPLANPs acts as a bioorthogonal handle allowing pretargeted single-photon emission computed tomography and radiotherapy, which revealed significantly enhanced tumor accumulation and minimal off-target toxicity in our experiments. The developed strategy showed a strong synergistic anti-cancer effect in vivo, with a tumor inhibition rate of up to 95.6% after 14 days of treatment. Our results suggest the potential of combining bioorthogonal pretargeted radiotherapy with suitable PSMA-targeted nanoparticles for the treatment of metastatic CRPC.