Analysis of the Impact of Ambulatory Care Based on Social Support on the Quality of Life of Patients with Graves' Ophthalmopathy.

Background: Graves' ophthalmopathy (GO) is an organ-specific autoimmune disease and is a common orbital condition that can possibly lead to blindness. Objective: Our aim was to find out how patients with GO are affected in terms of quality of life (QoL) by traditional nursing care and social support mobile care. Methods: A total of 38 patients with GO who were admitted to Beijing Chao-Yang Hospital in China between December 2018 and December 2023 underwent life evaluations before treatment, 6 weeks after treatment and 6 months after treatment. The control group comprised 27 patients and the experimental group comprised 11 patients. They were then split into 2 groups based on the European Group on Graves' Orbitopathy (EUGOGO) improvement criteria: improved and unimproved. Then, the mean value of the Graves' Ophthalmopathy-Quality of Life Inventory (GO-QOL) alterations were compared to see if there was any difference, and their post-treatment QoL was examined. Results: (1) Patients who improved in this study had a mean change in visual energy scale scores before and after treatment that was higher than the patients who did not (13.39 vs 0.00, respectively); (2) The social functioning scores on the GO-QOL scale increased by 17.05 points in the control group before and after treatment (P < .01); (3) A total of 15.4% of patients had a GO-QOL score >90 after therapy, indicating a significant impact on their lives. In the experimental group, scores on the visual power energy scale improved by 16.27 points after treatment compared with before treatment (P = .028). Conclusion: When used in conjunction with traditional treatment, social supportive mobile care improves the outcomes in patients with GO and is superior to traditional care on its own.

The immunosuppressive landscape in tumor microenvironment.

Recent advances in cancer immunotherapy, especially immune checkpoint inhibitors (ICIs), have revolutionized the clinical outcome of many cancer patients. Despite the fact that impressive progress has been made in recent decades, the response rate remains unsatisfactory, and many patients do not benefit from ICIs. Herein, we summarized advanced studies and the latest insights on immune inhibitory factors in the tumor microenvironment. Our in-depth discussion and updated landscape of tumor immunosuppressive microenvironment may provide new strategies for reversing tumor immune evasion, enhancing the efficacy of ICIs therapy, and ultimately achieving a better clinical outcome.

Effect of guar gum, gelatin, and pectin on moisture changes in freeze-dried restructured strawberry blocks.

This study aimed to investigate the effects of edible gum addition on moisture changes in freeze-dried restructured strawberry blocks (FRSB), which involved five groups: the control, 1.2% guar gum, 1.2% gelatin, 1.2% pectin, and the composite group with 0.5% guar gum, 0.5% gelatin, and 0.45% pectin. The results indicated that the drying rates of the five groups of FRSB presented similar early acceleration and later deceleration trends. Moisture content in FRSB was linearly predicted by peak area of low field nuclear magnetic resonance with R2 higher than 0.90 for all the five groups. The FRSB samples in the gelatin and composition groups formed a denser porous structure and had a lower hygroscopicity after four days of storage. This study provides a theoretical basis for controlling the processing of FRSB.

Changes and correlation analysis of volatile flavor compounds, amino acids, and soluble sugars in durian during different drying processes.

Durian contains rich flavor components that undergo complex changes during drying. In this study, durian was subjected to integrated freeze-drying (IFD), conventional freeze-drying (CFD), and hot air drying (AD). Compared with the fresh samples, those dried by IFD, CFD, and AD lost 11, 9, and 7 original volatile compounds, respectively, and generated 7, 6, and 8 new volatile compounds, respectively, and showed a rapid and then slow decreasing trend in the total content during drying. However, the types of amino acids and soluble sugars remained unchanged during each of the drying methods. Furthermore, volatile compounds showed a significant negative correlation with the majority of amino acids and a significant positive correlation with soluble sugars. The IFD samples had the highest content of volatile compounds, amino acids, and soluble sugars. Therefore, IFD is recommended as a preferable drying method for durian.

Tozasertib activates anti-tumor immunity through decreasing regulatory T cells in melanoma.

Although immune checkpoint therapy has significantly improved the prognosis of patients with melanoma, urgent attention still needs to be paid to the low patient response rates and the challenges of precisely identifying patients before treatment. Therefore, it is crucial to investigate novel immunosuppressive mechanisms and targets in the tumor microenvironment in order to reverse tumor immune escape. In this study, we found that the cell cycle checkpoint Aurora kinase B (AURKB) suppressed the anti-tumor immune response, and its inhibitor, Tozasertib, effectively activated T lymphocyte cytokine release in vitro and anti-tumor immunity in vivo. Tozasertib significantly inhibited melanoma xenograft tumor growth by decreasing the number of inhibitory CD4+ Treg cells in the tumors, which, in turn, activated CD8+ T cells. Single-cell analysis revealed that AURKB suppressed anti-tumor immunity by increasing MIF-CD74/CXCR4 signaling between tumor cells and lymphocytes. Our study suggests that AURKB is a newly identified anti-tumor immunity suppressor, whose inhibitors may be developed as novel anti-tumor immunity drugs and may have synergistic anti-melanoma effects with immune checkpoint therapies.

Rucaparib inhibits lung adenocarcinoma cell proliferation and migration via the SHCBP1/CDK1 pathway.

Src homolog and collagen homolog binding protein 1 (SHCBP1) binds to the SH2 domain of SHC-transforming protein 1 (SHC1) and is involved in midbody organization and cytokinesis completion. SHCBP1 has been reported to be a cancer driver gene, promoting cancer progression. However, the functional role and underlying mechanism of SHCBP1 in regulating lung adenocarcinoma (LUAD) cell proliferation and migration are incompletely understood. Here, we discovered that SHCBP1 is overexpressed in LUAD tissues and is associated with a poor prognosis. SHCBP1 knockdown inhibited LUAD cell proliferation and migration by arresting the cell cycle and preventing epithelial-mesenchymal transition (EMT) via decreasing cyclin-dependent kinase 1 (CDK1) expression. Mechanistically, CDK1 overexpression reversed SHCBP1 knockdown-induced inhibition of proliferation and migration, confirming CDK1 as a key downstream target of SHCBP1. In addition, we proposed that rucaparib may be a small-molecule inhibitor of SHCBP1 and validated both in vitro and in vivo that rucaparib inhibits cell proliferation and migration via suppression of the SHCBP1/CDK1 pathway in LUAD. Our study elucidates a newly identified role of SHCBP1 in promoting cell proliferation and migration in LUAD, and suggests rucaparib as a potential inhibitor for LUAD treatment.

A celastrol-based nanodrug with reduced hepatotoxicity for primary and metastatic cancer treatment.

BACKGROUND: Cancer is the world's leading cause of death and a key hindrance to extending life expectancy. Celastrol, a bioactive compound derived from Tripterygium wilfordii, has been shown to have excellent antitumor activity, but its poor solubility and severe organ toxicity side effects have hampered its clinical application. METHODS: In this study, a self-assembled nanodrug (PLC-NP) was designed to deliver celastrol to tumor sites while efficiently reducing its side effects by conjugating celastrol with the bioactive material LMWH and P-selectin targeting peptide (PSN). Extensive in vitro and in vivo experiments were performed to investigate both therapeutic efficacy and adverse effects. Furthermore, the specific mechanism of the antitumor activity has also been explored. FINDING: The PLC-NP nanodrugs were spherical in shape, with a mean particle size of 115.83 ± 6.93 nm. PLC-NP was sufficiently stable during blood circulation, with a selective target to P-selectin-highly expressed tumor cells, followed by releasing the containing celastrol under acidic environment and high levels of esterase in tumor cells. Both in vitro and in vivo results confirmed that celastrol's antitumor and anti-metastatic abilities were not attenuated and were actually strengthened after being formed into nanodrugs. More importantly, the organ toxicities of the modified celastrol nanodrug were dramatically reduced. Mechanistic study indicated that the inactivation of PI3K/Akt/mTOR signaling pathway and ROS-mediated mitochondrial dysfunction play critical roles in celastrol-mediated autophagy and apoptosis. INTERPRETATION: Our findings could offer a potential strategy for the translation of toxic compounds into clinical therapeutic nanomedicine. FUNDING: See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

Extracting the most discriminating functional connections in mild traumatic brain injury based on machine learning.

BACKGROUND: Mild traumatic brain injury (mTBI) is characterized as brain microstructural damage, which may cause a wide range of brain functional disturbances and emotional problems. Brain network analysis based on machine learning is an important means of neuroimaging research. Obtaining the most discriminating functional connection is of great significance to analyze the pathological mechanism of mTBI. METHODS: To better obtain the most discriminating features of functional connection networks, this study proposes a hierarchical feature selection pipeline (HFSP) composed of Variance Filtering (VF), Lasso, and Principal Component Analysis (PCA). Ablation experiments indicate that each module plays a positive role in classification, validating the robustness and reliability of the HFSP. Furthermore, the HFSP is compared with recursive feature elimination (RFE), elastic net (EN), and locally linear embedding (LLE), verifying its superiority. In addition, this study also utilizes random forest (RF), SVM, Bayesian, linear discriminant analysis (LDA), and logistic regression (LR) as classifiers to evaluate the generalizability of HFSP. RESULTS: The results show that the indexes obtained from RF are the highest, with accuracy = 89.74%, precision = 91.26%, recall = 89.74%, and F1 score = 89.42%. The HFSP selects 25 pairs of the most discriminating functional connections, mainly distributed in the frontal lobe, occipital lobe, and cerebellum. Nine brain regions show the largest node degree. LIMITATIONS: The number of samples is small. This study only includes acute mTBI. CONCLUSIONS: The HFSP is a useful tool for extracting discriminating functional connections and may contribute to the diagnostic processes.

Cu2-xSe nanoparticles suppress cell proliferation and migration in hepatocellular carcinoma by impairing mitochondrial respiration.

Cu2-xSe nanoparticles (Cu2-xSe NPs) as a new therapeutic drug platform is widely used in disease treatment due to their strong near-infrared optical absorption. In recent years, with their continuous expansion of applications in different fields, their own biological effects have received increasing attention. However, little is known about the effect of Cu2-xSe NPs on cancer cell. In this research, we found that Cu2-xSe NPs inhibited proliferation of HepG2 cells (IC50: 15.91µM) and SMMC-7721 cells (IC50: 43.15µM) and they mainly induced cell cycle arrest at the G2/M phase. Moreover, Cu2-xSe NPs inhibited HepG2 and SMMC-7721 cell migration and lamellopodia formation. Further studies indicated that Cu2-xSe NPs impaired mitochondrial respiration by inhibiting electron transport chain complex activity, thus reducing adenosine triphosphate levels. The insufficient energy supply subsequently impaired actin cytoskeleton assembly, ultimately inhibiting HepG2 and SMMC-7721 cell proliferation and migration. These findings suggest that Cu2-xSe NPs may have potentially antitumor activity, which might provide new insights of NPs into specific cancer treatment.

mTBI-DSANet: A deep self-attention model for diagnosing mild traumatic brain injury using multi-level functional connectivity networks.

The main approach for analyzing resting-state functional magnetic resonance imaging (rs-fMRI) is the low-order functional connectivity network (LoFCN) based on the correlation between two brain regions. Based on LoFCN, researchers recently proposed the topographical high-order FCN (tHoFCN) and the associated high-order FCN (aHoFCN) to explore the high-order interactions among brain regions. In this work, we designed a Deep Self-Attention (DSA) framework called mTBI-DSANet to diagnose mild traumatic brain injury (mTBI) using multi-level FCNs, including LoFCN, tHoFCN, and aHoFCN. The multilayer perceptron and self-attention mechanism in mTBI-DSANet were designed to capture important features for the mTBI diagnosis. We evaluated the mTBI-DSANet's performance on the real rs-fMRI dataset, which was collected by Third Xiangya Hospital of Central South University from April 2014 to February 2021. We compared the performance of mTBI-DSANet with distinct FCNs and their combinations under 10-fold cross-validation. Based on the LoFCN+aHoFCN combination, the average performance of mTBI-DSANet achieved the best accuracy of 0.834, which is significantly better than peer methods. The experiments demonstrated the potential of the mTBI-DSANet in assisting mTBI diagnosis.

The Carbon Emission Characteristics and Reduction Potential in Developing Areas: Case Study from Anhui Province, China.

Global warming and world-wide climate change caused by increasing carbon emissions have attracted a widespread public attention, while anthropogenic activities account for most of these problems generated in the social economy. In order to comprehensively measure the levels of carbon emissions and carbon sinks in Anhui Province, the study adopted some specific carbon accounting methods to analyze and explore datasets from the following suggested five carbon emission sources of energy consumption, food consumption, cultivated land, ruminants and waste, and three carbon sink sources of forest, grassland and crops to compile the carbon emission inventory in Anhui Province. Based on the compiled carbon emission inventory, carbon emissions and carbon sink capacity were calculated from 2000 to 2019 in Anhui Province, China. Combined with ridge regression and scenario analysis, the STIRPAT model was used to evaluate and predict the regional carbon emission from 2020 to 2040 to explore the provincial low-carbon development pathways, and carbon emissions of various industrial sectors were systematically compared and analyzed. Results showed that carbon emissions increased rapidly from 2000 to 2019 and regional energy consumption was the primary source of carbon emissions in Anhui Province. There were significant differences found in the increasing carbon emissions among various industries. The consumption proportion of coal in the provincial energy consumption continued to decline, while the consumption of oil and electricity proceeded to increase. Furthermore, there were significant differences among different urban and rural energy structures, and the carbon emissions from waste incineration were increasing. Additionally, there is an inverted "U"-shape curve of correlation between carbon emission and economic development in line with the environmental Kuznets curve, whereas it indicated a "positive U"-shaped curve of correlation between carbon emission and urbanization rate. The local government should strengthen environmental governance, actively promote industrial transformation, and increase the proportion of clean energy in the energy production and consumption structures in Anhui Province. These also suggested a great potential of emission reduction with carbon sink in Anhui Province.

Relationship between job stress, thinking style and symptoms of post-traumatic stress disorder in mental health nurses.

Introduction: Mental health nurses are often exposed to stressful events which may lead to feeling of stress in their daily work, and this feeling has a profound impact on nurses' mental health. Aim: This study aimed to evaluate the relationship between job stress, thinking style and symptoms of post-traumatic stress disorder (PTSD) of mental health nurses, and to explore the mechanism of job stress and thinking style on symptoms of PTSD. Method: This cross-sectional study collected related data of 351 mental health nurses in China, and the data was analyzed by PROCESS macro for SPSS. Results: The results showed that 18.2% of mental health nurses had the symptoms of PTSD. Thinking style (monarchic thinking style, anarchic thinking style and external thinking style) played a moderating role in the predictive effects of job stress on the symptoms of PTSD. Discussion: The research pointed out the relationship between job stress and symptom of PTSD, and clarified the critical role of thinking style among mental health nurses. Implications for practice: It is recommended that organizations should enact effective policy and intervention programs to reduce job stress and PTSD symptoms of mental health nurses which may improve their mental health level.

Cephalosporin C biosynthesis and fermentation in Acremonium chrysogenum.

Cephalosporins are currently the most widely used antibiotics in clinical practice. The main strain used for the industrial production cephalosporin C (CPC) is Acremonium chrysogenum. CPC has the advantages of possessing a broad antibacterial spectrum and strong antibacterial activity. However, the yield and titer of cephalosporins obtained from A. chrysogenum are much lower than penicillin, which is also a ß-lactam antibiotic produced by Penicillium chrysogenum. Molecular biology research into A. chrysogenum has focused on gene editing technologies, multi-omics research which has provided information on the differences between high- and low-yield strains, and metabolic engineering involving different functional genetic modifications and hierarchical network regulation to understand strain characteristics. Furthermore, optimization of the fermentation process is also reviewed as it provides the optimal environment to realize the full potential of strains. Combining rational design to control the metabolic network, high-throughput screening to improve the efficiency of obtaining high-performance strains, and real-time detection and controlling in the fermentation process will become the focus of future research in A. chrysogenum. This minireview provides a holistic and in-depth analysis of high-yield mechanisms and improves our understanding of the industrial value of A. chrysogenum. KEY POINTS: • Review of the advances in A. chrysogenum characteristics improvement and process optimization • Elucidate the molecular bases of the mechanisms that control cephalosporin C biosynthesis and gene expression in A. chrysogenum • The future development trend of A. chrysogenum to meet industrial needs.

A Dynamic Bayesian Model for Breast Cancer Survival Prediction.

OBJECTIVE: Predicting breast cancer survival and targeting patients at high-risk of mortality is of crucial importance. METHODS: We built a Bayesian Dynamic Cox (BDCox) model for predicting 5-year overall survival in breast cancer patients using data of the SEER Cancer Registry with 12,840 women. Four feature selection methods were used to identify predictors and enhance parsimony: fast backward variable selection, elastic net, Bayesian Model Average (BMA), and clinical expertise. All resulting models and a baseline full model containing all features were internally validated via bootstrapping and externally validated in the Shanghai Breast Cancer Survival Study. RESULTS: BMA outperformed other feature selection methods in both internal and external validations. The BDCox model with 12 predictors had the best performance. Several predictors showed time-varying associations with survival that are in agreement with previous studies. CONCLUSION: The model developed using BDCox outperformed other prognostic models considered in our study. The internal validation results indicate that the BDCox model is capable of achieving high prediction accuracy (C-statistic: 0.802), and the external validation results showed excellent generalizability of the BDCox model (C-statistic: 0.739). SIGNIFICANCE: We built a dynamic Bayesian model from the large population-based registry SEER for predicting 5-year breast cancer overall survival. The prediction performance of the BDCox model is significantly better than other survival models.

Stigma and Peer-Led Interventions: A Systematic Review and Meta-Analysis.

Purpose: The main purpose of our systematic review was to investigate the effect of peer-led intervention on self-stigma in individuals with mental health problems. Secondary purpose was investigating the impact of peer intervention on clinical symptoms, recovery-related outcomes, and disclosure-related outcomes. Methods: Five electronic databases were searched from 1975 to 2021. Literature databases were searched for randomized controlled trials. From the perspective of key outcomes, a meta-analysis of the effects of peer-led interventions on changing stigma was conducted. Results: A meta-analysis of randomized controlled trials targeting different target groups with mental health problems (e.g., adolescents, college students, family members of mentally ill persons, unemployed persons, etc.) was conducted. It was found that, at the end of the intervention, intervention had a positive effect on main outcomes such as self-stigma and stress from stigma. As for secondary outcomes, there was no significant influence on clinical symptoms. There was a positive effect on rehabilitation and empowerment, but without a statistical significance. There was a statistically significant effect on self-efficacy and professional help seeking. There was a statistically significant effect on confidentiality and disclosure-related distress in the Honest Open Proud (HOP) subgroup. There was no significant influence on confidentiality and withdrawal in the non-HOP subgroup. Conclusion: Peer-led intervention can reduce self-stigma and stigma pressure and might improve recovery and empowerment. It increases self-efficacy and willingness to seek professional help, but has no significant effect on clinical symptoms and withdrawal. HOP intervention has positive effects on disclosure-related confidentiality and pain. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO, identifier: CRD42021287584.

Research Advances on Suppressor of Cytokine Signaling 3 (SOCS3) in Animal Carbohydrate and Lipid Metabolism Processes.

The SOCS3 proteins played important roles in regulating the energy metabolism processes. They are crucial intracellular inhibitors related to animal obesity, immunity and inflammation. This makes SOCS3 genes very important in animal genetics and breeding. The research was conducted to investigate and explore the recent advance in the present studies on SOCS3 in animal energy and lipid metabolism processes. All the references were carefully retrieved from the PubMed database by searching key words "suppressor of cytokine signaling (SOCS)", "SOCS3", "animal carbohydrate metabolism", "animal lipid metabolism", "animal energy metabolism", "insulin resistance", "leptin", "obesity", "SOCS*" and "AMPK". All the related references retrieved were initially screened and fully reviewed for manual inspection. This effort intends to get a quick understanding and make insights into the mechanisms of Suppressor of Cytokine Signaling 3 (SOCS3) and their molecular interactions with the other cellular proteins. In this review, it was found that SOCS3 proteins could regulate cytokine receptors' signal transduction mainly through the JAK/STAT and GH/IGF-I and mTOR-STAT3-SOCS3 signaling pathways, whereas the genetic mutations or knockouts of SOCS3 genes had significant effects on animal energy metabolism. The review summarized all the relevant research reports on SOCS3 in the animal carbohydrate and lipid metabolism processes, which can provide practical reference for the genetic breeding of high-quality domestic animal breeds. It is also of great significance to further research on the genetic regulation mechanism of SOCS3 genes affecting energy metabolism and the well development of the animal breeding system.

Effective Triple-Negative Breast Cancer Targeted Treatment Using iRGD-Modified RBC Membrane-Camouflaged Nanoparticles.

INTRODUCTION: Triple-negative breast cancer (TNBC) has the high degree of malignancy and aggressiveness. There is no targeted therapy drug. Many studies have shown that RBC membrane-coated nanoparticles achieve biological camouflage. In addition, the RGD module in the iRGD mediates the penetration of the vector across the tumor blood vessels to the tumor tissue space. Therefore, we developed iRGD-RM-(DOX/MSNs) by preparing MSNs loaded with doxorubicin as the core, and coating the surface of the MSNs with iRGD-modified RBC membranes. METHODS: iRGD-RM-(DOX/MSNs) were fabricated using physical extrusion. In addition, their physical and chemical characterization, hemolytic properties, in vivo acute toxicity and inflammatory response, in vitro and in vivo safety, and qualitative and quantitative cellular uptake by RAW 264.7 cells and MDA-MB-231 cells were evaluated and compared. Furthermore, we examined the antitumor efficacy of iRGD-RM-(DOX/MSN) nanoparticles in vitro and in vivo. RESULTS: iRGD-RM-(DOX/MSNs) have reasonable physical and chemical properties. iRGD-RM-(DOX/MSNs) escaped the phagocytosis of immune cells and achieved efficient targeting of nanoparticles at the tumor site. The nanoparticles showed excellent antitumor effects in vivo and in vitro. CONCLUSION: In this study, we successfully developed biomimetic iRGD-RM-(DOX/MSNs) that could effectively target tumors and provide a promising strategy for the effective treatment of TNBC.

Spatial and temporal differentiation and influencing factors of environmental governance performance in the Yangtze River Delta, China.

As the development of Yangtze River Delta urban agglomeration has been upgraded to a national level development strategy in China, relevant regions need to pay more attention to the environmental governance issues. Based on the 2013-2018 development data of 41 cities and the established evaluation indicator system with "press-state-response" (PSR) model, we mainly use a combination of global principal component analysis (GPCA) and entropy method to comprehensively measure regional environmental governance performance (EGP) in the Yangtze River Delta urban agglomeration. Next, the spatial relationship is explored and discussed with spatial autocorrelation analysis. Finally, the panel Tobit model is used to perform a regression analysis on the factors affecting the performance of environmental governance in the Yangtze River Delta region. The results are summarized as follows. (1) From 2013 to 2018, the overall environmental governance performance of the Yangtze River Delta region maintained a steady growth trend, of which the environmental governance performance of Jiangsu Province and Shanghai maintained a steady increase, and the environmental governance performance of Anhui and Zhejiang Province fluctuated greatly. (2) These cities with better EGP are mainly located in the central and southern regions of the Yangtze River Delta, and those cities with poor EGP are mainly located in the northern part of the Yangtze River Delta. The environmental governance performance gap between provinces and cities is obviously large, and there are significant spatial positive correlations, spatial spillover effects and a trend of agglomeration with increased volatility. (3) The regression analysis shows that the economic development level has a significant positive impact on the EGP of the Yangtze River Delta region. Meanwhile, the negative impact of industrial structure and foreign investment is significant, but the positive impact of R&D investment intensity is insignificant, on the performance of environmental governance in the Yangtze River Delta region.

Platelet Membrane-Coated and VAR2CSA Malaria Protein-Functionalized Nanoparticles for Targeted Treatment of Primary and Metastatic Cancer.

Metastasis is the main cause of death in cancer patients. The efficacy of pharmacological therapy for cancer is limited by the heterogeneous nature of cancer cells and the lack of knowledge of microenvironments in metastasis. Evidence has shown that activated platelets possess both tumor-homing and metastasis-targeting properties via intrinsic cell adhesion molecules on platelets, and malaria protein VAR2CSA is able to specifically bind to oncofetal chondroitin sulfate, which is overexpressed on cancer cells with both epithelial and mesenchymal phenotypes. Inspired by these mechanisms, we developed a recombinant VAR2CSA peptide (rVAR2)-modified activated platelet-mimicking nanoparticles (rVAR2-PM/PLGA-ss-HA) by coating the surface of disulfide-containing biodegradable PLGA conjugate nanoparticles (PLGA-ss-HA) with an activated platelet membrane. The results demonstrated that the engineered 122 nm rVAR2-PM/PLGA-ss-HA inherited the innate properties of the activated platelet membrane and achieved enhanced homing to both primary and metastatic foci. The nanoparticles were endocytosed and responded to a high intracellular concentration of reduced glutathione, resulting in nanoparticle disintegration and the release of chemotherapeutic drugs to kill tumor cells. Thus, rVAR2-decorated activated platelet-targeting nanoparticles with controlled drug release provide a promising drug delivery strategy for efficient treatment of primary and metastatic cancer.