Flare: An FPGA-Based Full Precision Low Power CNN Accelerator with Reconfigurable Structure.

Convolutional neural networks (CNNs) have significantly advanced various fields; however, their computational demands and power consumption have escalated, posing challenges for deployment in low-power scenarios. To address this issue and facilitate the application of CNNs in power constrained environments, the development of dedicated CNN accelerators is crucial. Prior research has predominantly concentrated on developing low precision CNN accelerators using code generated from high-level synthesis (HLS) tools. Unfortunately, these approaches often fail to efficiently utilize the computational resources of field-programmable gate arrays (FPGAs) and do not extend well to full precision scenarios. To overcome these limitations, we integrate vector dot products to unify the convolution and fully connected layers. By treating the row vector of input feature maps as the fundamental processing unit, we balance processing latency and resource consumption while eliminating data rearrangement time. Furthermore, an accurate design space exploration (DSE) model is established to identify the optimal design points for each CNN layer, and dynamic partial reconfiguration is employed to maximize each layer's access to computational resources. Our approach is validated through the implementation of AlexNet and VGG16 on 7A100T and ZU15EG platforms, respectively. We achieve an average convolutional layer throughput of 28.985 GOP/s and 246.711 GOP/s for full precision. Notably, the proposed accelerator demonstrates remarkable power efficiency, with a maximum improvement of 23.989 and 15.376 times compared to current state-of-the-art FPGA implementations.

Pseudomonas aeruginosa isolation is an important predictor for recurrent hemoptysis after bronchial artery embolization in patients with idiopathic bronchiectasis: a multicenter cohort study.

BACKGROUND: Nearly half of bronchiectasis patients receiving bronchial artery embolization (BAE) still have recurrent hemoptysis, which may be life-threatening. Worse still, the underlying risk factors of recurrence remain unknown. METHODS: A retrospective cohort was conducted of patients with idiopathic bronchiectasis who received BAE from 2015 to 2019 at eight centers. Patients were followed up for at least 24 months post BAE. Based on the outcomes of recurrent hemoptysis and recurrent severe hemoptysis, a Cox regression model was used to identify risk factors for recurrence. RESULTS: A total of 588 individuals were included. The median follow-up period was 34.0 months (interquartile range: 24.3-53.3 months). The 1-month, 1-year, 2-year, and 5-year cumulative recurrent hemoptysis-free rates were 87.2%, 67.5%, 57.6%, and 49.4%, respectively. The following factors were relative to recurrent hemoptysis: 24-h sputum volume (hazard ratio [HR] = 1.99 [95% confidence interval [95% CI]: 1.25-3.15, p = 0.015]), isolation of Pseudomonas aeruginosa (HR = 1.50 [95% CI: 1.13-2.00, p = 0.003]), extensive bronchiectasis (HR = 2.00 [95% CI: 1.29-3.09, p = 0.002]), and aberrant bronchial arteries (AbBAs) (HR = 1.45 [95% CI: 1.09-1.93, p = 0.014]). The area under the receiver operating characteristic curve of the nomogram was 0.728 [95% CI: 0.688-0.769]. CONCLUSIONS: Isolation of Pseudomonas aeruginosa is an important independent predictor of recurrent hemoptysis. The clearance of Pseudomonas aeruginosa might effectively reduce the hemoptysis recurrence rate.

Fast Determination of Optimal Transmission Rate for Wireless Blockchain Networks: A Graph Convolutional Neural Network Approach.

One of the primary challenges in wireless blockchain networks is to ensure security and high throughput with constrained communication and energy resources. In this paper, with curve fitting on the collected blockchain performance dataset, we explore the impact of the data transmission rate configuration on the wireless blockchain system under different network topologies, and give the blockchain a utility function which balances the throughput, energy efficiency, and stale rate. For efficient blockchain network deployment, we propose a novel Graph Convolutional Neural Network (GCN)-based approach to quickly and accurately determine the optimal data transmission rate. The experimental results demonstrate that the average relative deviation between the blockchain utility obtained by our GCN-based method and the optimal utility is less than 0.21%.

Co-deficiency of B7-H3 and B7-H4 identifies high CD8 + T cell infiltration and better prognosis in pancreatic cancer.

BACKGROUND: Immunotherapy is a novel hotspot for the treatment of pancreatic adenocarcinoma (PAAD). However, potential biomarkers which could identify the inflamed tumor microenvironment (TME) are urgently required. METHODS: In the present study, we measured the levels of B7-H3, B7-H4, and major tumor-infiltrating immune cells (TIICs) using bioinformatics analyses and immunohistochemistry (IHC) staining on PAAD samples represented in the tissue microarray (TMA) format. Statistical analysis and figures exhibition were performed using R 4.1.0, SPSS 26.0, and GraphPad Prism 6.0. RESULTS: B7-H3 and B7-H4 were up-regulated in PAAD compared with para-tumor tissues, and their expression exhibited no tight correlation in PAAD tissues. B7-H3 and B7-H4 were lowly expressed in well-differentiated PAAD tissues and correlated with poorly differentiated grades. Besides, single B7-H3 or B7-H4 expression exhibited limited prognostic value, but co-deficiency of B7-H3 and B7-H4 predicted a better prognosis in PAAD. Moreover, co-deficiency of B7-H3 and B7-H4 indicated immuno-hot tumors with high CD8 + T cell infiltration. CONCLUSIONS: Overall, combined B7-H3 and B7-H4 expression is a promising stratification strategy to assess prognosis and immunogenicity in PAAD, which could be used as a novel classifier in clinical practice.

Research on Risk Contagion among Financial Submarkets in China Based on Complex Networks.

As the COVID-19 outbreak has an impact on the global economy, there will be interest in how China's financial markets function during the outbreak. To investigate the path of risk contagion in China's financial sub-markets before and after the COVID-19 outbreak, we divided the 2016-2021 period into two phases. Based on the time of the COVID-19 outbreak, we divided the new stage of economic development into pre-epidemic and post-epidemic stages and employed the DCC-GARCH model to investigate the dynamic correlation coefficients among the financial sub-markets in China. Furthermore, we employed complex network theory and the minimum tree model to describe the risk contagion path between two-stage Chinese financial submarkets. Finally, we provided pertinent recommendations for investors and policymakers and conducted a brief discussion based on the findings of the research.

Mindfulness and burnout among bedside registered nurses: A cross-sectional study.

Nursing is a high stress job, and burnout of nurses is of particular concern. The aim of this cross-sectional survey study was to examine the relationship between mindfulness and burnout, and how the mindfulness facets vary in their associations with the different domains of burnout for Chinese nurses. A sample of registered bedside nurses working in a tertiary Chinese hospital (n = 763) was surveyed from February to June 2017 regarding mindfulness (i.e. acting with awareness, describing, and non-judging of experiences), burnout (i.e. emotional exhaustion, depersonalization, and personal accomplishment), and sociodemographic and job-related characteristics. Higher scores on the three facets of mindfulness were associated with less emotional exhaustion and depersonalization, and acting with awareness showed the highest regression coefficients. Personal accomplishment was positively associated with acting with awareness and describing, whereas it was negatively related to non-judging of experiences. Describing was the strongest facet associated with personal accomplishment. In conclusion, there were clearly correlations between mindfulness as a personal trait and burnout among Chinese bedside nurses. These findings suggest the potential benefits of tailored mindfulness-based interventions in reducing nurse burnout in China.

Reference image based phase unwrapping framework for a structured light system.

A novel real-time full-field phase unwrapping framework is proposed for the one-projector and one-camera structured light system. In this framework, only four patterns (including three fringe patterns and a binary speckle pattern) are required to measure the absolute 3D shape of the targets. We use the structured light system to capture four images of a nearly planar target (e.g. wall), of which the speckle image is taken as the reference image, and the corresponding absolute phase map is computed and stored, before measuring. So each pixel in the reference image can be mapped to an absolute phase value. In this way, if we can create the correspondences between the current and the reference speckle images in the process of measurement by using a matching algorithm, we can directly map the absolute values for the pixels of the current image. The mapped absolute phases can be used to determine the period of the relative phases. The experimental results verified the effectiveness and efficiency of the proposed framework. On a consumer-grade GPU (Nvidia GTX1060), our method can run at 187 fps.

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach.

The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ -equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.

Graph Convolutional Networks With Adaptive Neighborhood Awareness.

Graph convolutional networks (GCNs) can quickly and accurately learn graph representations and have shown powerful performance in many graph learning domains. Despite their effectiveness, neighborhood awareness remains essential and challenging for GCNs. Existing methods usually perform neighborhood-aware steps only from the node or hop level, which leads to a lack of capability to learn the neighborhood information of nodes from both global and local perspectives. Moreover, most methods learn the nodes' neighborhood information from a single view, ignoring the importance of multiple views. To address the above issues, we propose a multi-view adaptive neighborhood-aware approach to learn graph representations efficiently. Specifically, we propose three random feature masking variants to perturb some neighbors' information to promote the robustness of graph convolution operators at node-level neighborhood awareness and exploit the attention mechanism to select important neighbors from the hop level adaptively. We also utilize the multi-channel technique and introduce a proposed multi-view loss to perceive neighborhood information from multiple perspectives. Extensive experiments show that our method can better obtain graph representation and has high accuracy.

Adaptive Fuzzy Tracking Control With Global Prescribed-Time Prescribed Performance for Uncertain Strict-Feedback Nonlinear Systems.

For strict-feedback systems with mismatched uncertainties, adaptive fuzzy control techniques are developed to provide global prescribed performance with prescribed-time convergence. First, a class of prescribed-time prescribed performance functions are designed to quantify the performance constraints of the tracking error. Additionally, a novel error transformation function is provided to eliminate the initial value limitations and resolve the singularity issue in previous research. To ensure the convergence of the tracking error into a prescribed bounded region within a prescribed time and satisfactory transient performance, controllers with or without approximating structures are established. Notably, the settling time and initial condition of the prescribed performance function are completely independent of the initial tracking error and system parameters, thereby improving upon existing results. Furthermore, the disadvantage of the semi-global boundedness of tracking error induced by dynamic surface control can be eliminated through the use of a novel Lyapunov-like energy function. Finally, the effectiveness of the proposed strategies is validated through numerical simulations performed on practical examples.

2D petal-like PdAg nanosheets promote efficient electrocatalytic oxidation of ethanol and methanol.

The development of efficient alcohol electrooxidation catalysts is of vital importance for the commercialization of direct liquid fuel cells. As emerging advanced catalysts, two-dimensional (2D) noble metal nanomaterials have attracted much research attention due to their intrinsic structural advantages. Herein, we report the synthesis of petal-like PdAg nanosheets (NSs) with an ultrathin 2D structure and jagged edges via a facile wet-chemical approach, combining doping engineering and morphology tuning. Notably, the highly active sites and Pd-Ag composition endowed PdAg NSs with improved toxicity tolerance and substantially improved the durability toward the ethanol/methanol oxidation reaction (EOR/MOR). Moreover, the electronic effect and synergistic effect significantly enhanced the EOR and MOR activities in comparison with Pd NSs and commercial Pd/C. This work provides efficient catalysts for fuel electrooxidations and deep insight into the rational design and fabrication of novel 2D nanoarchitecture.

Ginsenoside Rh2 enhances immune surveillance of natural killer (NK) cells via inhibition of ERp5 in breast cancer.

BACKGROUND: One critical component of the immune system that prevents breast cancer cells from forming distant metastasis is natural killer (NK) cells participating in immune responses to tumors. Ginsenoside Rh2 (GRh2) as one of the major active ingredients of ginseng has been employed in treatment of cancers, but the function of GRh2 in modulating the development of breast cancer remains elusive. PURPOSE: This study was to dissect the effect of GRh2 against breast cancer and its potential mechanisms associated with NK cells, both in vitro and in vivo. METHODS: MDA-MB-231 and 4T1 cells were used to establish in situ and hematogenous mouse models. MDA-MB-231 and MCF-7 were respectively co-cultured with NK92MI cells or primary NK cells in vitro. Anti-tumor efficacy of GRh2 was verified by immunohistochemistry (IHC), Cell Counting Kit-8 (CCK8), high resolution micro-computed tomography (micro-CT) scanning of lungs and hematoxylin and eosin (H&E) staining. Lactate dehydrogenase (LDH) cytotoxicity assay, flow cytometry, in vivo depletion of NK cells, enzyme-linked immunosorbent assay (ELISA), western blot, quantitative reverse transcription polymerase chain reaction (qRT-PCR), immunofluorescence and cell transfection were performed for investigating the anti-tumor mechanisms of GRh2. Molecular docking, microscale thermophoresis (MST) and cellular thermal shift assay (CETSA) were employed to determine the binding between endoplasmic reticulum protein 5 (ERp5) and GRh2. RESULTS: We demonstrated that GRh2 exerted prominent impacts on retarding the growth and metastasis of breast cancer through boosting the cytotoxic function of NK cells, as validated by the elevated release of perforin, granzyme B and interferon-γ (IFN-γ). Mechanistical studies revealed that GRh2 was capable of diminishing the expression of ERp5 and GRh2 directly bound to ERp5 in MDA-MB-231 cells as well as on a recombinant protein level. GRh2 prevented the formation of soluble MICA (sMICA) and upregulated the expression level of MICA in vivo and in vitro. Importantly, the reduced lung metastasis of breast cancer by GRh2 was almost abolished upon the depletion of NK cells. Moreover, GRh2 was able to insert into the binding pocket of ERp5 directly. CONCLUSION: We firstly demonstrated that GRh2 played a pivotal role in augmenting NK cell activity by virtue of modulating the NKG2D-MICA signaling axis via directly binding to ERp5, and may be further optimized to a therapeutic agent for the treatment of breast cancer.

Inhibition of LPS-Induced Skin Inflammatory Response and Barrier Damage via MAPK/NF-κB Signaling Pathway by Houttuynia cordata Thunb Fermentation Broth.

Houttuynia cordata Thunb is rich in active substances and has excellent antioxidant and anti-inflammatory activity. Scanning electron microscopy and gel permeation chromatography were used to analyze the molecular characteristics of the fermentation broth of Houttuynia cordata Thunb obtained through fermentation with Clavispora lusitaniae (HCT-f). The molecular weight of HCT-f was 2.64265 × 105 Da, and the polydispersity coefficient was 183.10, which were higher than that of unfermented broth of Houttuynia cordata Thunb (HCT). By investigating the active substance content and in vitro antioxidant activity of HCT-f and HCT, the results indicated that HCT-f had a higher active substance content and exhibited a superior scavenging effect on 2,2-diphenyl-1-picrylhydrazyl radicals and hydroxyl radicals, with IC50 values of 11.85% and 9.01%, respectively. Our results showed that HCT-f could effectively alleviate the increase in the secretion of inflammatory factors and apoptotic factors caused by lipopolysaccharide (LPS) stimulation, and had a certain effect on repairing skin barrier damage. HCT-f could exert an anti-inflammatory effect by down-regulating signaling in the MAPK/NF-κB pathway. The results of erythrocyte hemolysis and chicken embryo experiments showed that HCT-f had a high safety profile. Therefore, this study provides a theoretical basis for the application of HCT-f as an effective ingredient in food and cosmetics.

A quadrivalent recombinant influenza Hemagglutinin vaccine induced strong protective immune responses in animal models.

Globally, influenza poses a substantial threat to public health, serving as a major contributor to both morbidity and mortality. The current vaccines for seasonal influenza are not optimal. A novel recombinant hemagglutinin (rHA) protein-based quadrivalent seasonal influenza vaccine, SCVC101, has been developed. SCVC101-S contains standard dose protein (15µg of rHA per virus strain) and an oil-in-water adjuvant, CD-A, which enhances the immunogenicity and cross-protection of the vaccine. Preclinical studies in mice, rats, and rhesus macaques demonstrate that SCVC101-S induces robust humoral and cellular immune responses, surpassing those induced by commercially available vaccines. Notably, a single injection with SCVC101-S can induce a strong immune response in macaques, suggesting the potential for a standard-dose vaccination with a recombinant protein influenza vaccine. Furthermore, SCVC101-S induces cross-protection immune responses against heterologous viral strains, indicating broader protection than current vaccines. In conclusion, SCVC101-S has demonstrated safety and efficacy in preclinical settings and warrants further investigation in human clinical trials. Its potential as a valuable addition to the vaccines against seasonal influenza, particularly for the elderly population, is promising.

The relationship between social and psychological factors with cognitive impairment after stroke: a prospective study.

Objectives: To investigate the association between social and psychological factors and the risk of cognitive impairment following acute ischemic stroke. Materials and methods: A prospective study was conducted at Shanghai Tenth People's Hospital from June 2021 to July 2022. The study focused on social and psychological factors, which were assessed using the Social Support Rating Scale (SSRS), Self-Perceived Burden Scale (SPBS), and Hamilton Depression Scale (HAMD) within 3 days after admission to the hospital. Cognitive function was evaluated using the Montreal Cognitive Assessment at 3 months post-stroke. Logistic hierarchical regression models were used to examine the association between these three indicators and cognitive impairment following a stroke. Results: Among these patients, cognitive function was assessed in 211 cases at the 3-month follow-up after the initial stroke event. At 3 months post-stroke, 118(55.9%) of the participants experienced cognitive impairment, while 93(44.1%) did not. The scores on the SPBS and HAMD showed significant associations with cognitive impairment at 3 months after stroke. The scores of SPBS [scores: 30~39 vs.<20 points, odds ratio (OR)=2.993 (1.135-7.896); scores: ≥40 vs.<20points, OR=7.382 (1.117-48.799); P=0.043] and the HAMD [scores: >7 vs.≤7 points, OR=3.287(1.362~7.936); P=0.008]. There were no significant associations observed between SSRS and PSCI. Conclusion: Early screening for depressive symptoms and focusing on self-perceived burden can be beneficial for decision support for clinicians and improve cognitive function recovery at the 3-month mark post-stroke.

[Analysis of hemoptysis treated by bronchial arterial embolization].

OBJECTIVE: To investigate the correlation of effect of bronchial arterial embolization (BAE) in the treatment of hemoptysis and relative factors. METHODS: From December 2007 to August 2011, 105 patients with hemoptysis were admitted. BAE was carried out after bronchial artery arteriography and ensured bronchial artery anomaly. Patients were followed up 3 to 24 months. RESULTS: All 105 cases were confirmed abnormal bronchial artery. And 101 cases (96.2%) were completed BAE, and among them, 91 cases (86.7%) were stop bleeding , and 7 cases (6.7%) were excellence. The total effective rate was 93.4%.In follow-up period, there were 69 cases (65.7%) without recurrence, and 8 cases (7.6%) were recent recurrence and 10 cases (9.5%) were long-term recurrence, respectively. All factors were no obvious correlation to effect of BAE. CONCLUSION: BAE is an effective treatment for hemoptysis.Effect of the BAE was irrespective to related factors.

Analysis of the relationship between supply-demand matching of selected ecosystem services and urban spatial governance: a case study of Suzhou, China.

The mismatch between the supply and demand of ecosystem services has become a critical cause of the decline of urban ecological security. Studying the supply-demand matching of ecosystem services and exploring its association with urban spatial governance are imperative for ensuring sustainable urbanization. Taking Suzhou City as a case, the supply and demand values and matching degrees of five selected ecosystem services were assessed. Additionally, we explored the relationship between ecosystem services and urban spatial governance, with a focus on urban functional zoning. The findings indicate that first, the supply value of water production, food production, carbon sequestration, and tourism and leisure fall short of the demand value, while the supply value of air purification exceeds the demand value. The spatial matching of supply and demand shows a typical circular structure, with areas in short supply predominantly located in the downtown area and its vicinity. Second, the degree of coupling coordination between the supply-demand ratio of selected ecosystem services and the intensity of ecological control is low. Urban functional zoning can affect the supply-demand relationship of selected ecosystem services, and intensified development efforts can exacerbate the mismatch between supply and demand. Third, research on the supply-demand matching of selected ecosystem services can facilitate the assessment and regulation of urban functional zoning. Urban spatial governance can be regulated based on land use, industry, and population, with a focus on achieving a better supply-demand matching of ecosystem services. Through the analysis, this paper is aimed to provide reference for mitigating urban environmental problems and formulating sustainable urban development strategies.

A Multichannel Convolutional Decoding Network for Graph Classification.

Graph convolutional networks (GCNs) have shown superior performance on graph classification tasks, and their structure can be considered as an encoder-decoder pair. However, most existing methods lack the comprehensive consideration of global and local in decoding, resulting in the loss of global information or ignoring some local information of large graphs. And the commonly used cross-entropy loss is essentially an encoder-decoder global loss, which cannot supervise the training states of the two local components (encoder and decoder). We propose a multichannel convolutional decoding network (MCCD) to solve the above-mentioned problems. MCCD first adopts a multichannel GCN encoder, which has better generalization than a single-channel GCN encoder since different channels can extract graph information from different perspectives. Then, we propose a novel decoder with a global-to-local learning pattern to decode graph information, and this decoder can better extract global and local information. We also introduce a balanced regularization loss to supervise the training states of the encoder and decoder so that they are sufficiently trained. Experiments on standard datasets demonstrate the effectiveness of our MCCD in terms of accuracy, runtime, and computational complexity.

Risk Correlation Analysis between Polycystic Ovary Syndrome (PCOS) and Serum Visfatin Levels in Middle-Aged Women: Systematic Review and Meta-Analysis.

BACKGROUND: Polycystic ovary syndrome (PCOS) is an endocrine disorder that occurs frequently in women of childbearing age and is associated with insulin resistance. Serum visfatin can affect insulin resistance by binding to insulin receptors and further affect the occurrence and development of PCOS. In this study, we investigated the current status of serum visfatin levels in patients with PCOS through a literature search and meta-analysis. METHODS: We searched online Pubmed, Embase, Web of Science, the Cochrane Library, CNKI (China National Knowledge Infrastructure), CBMdisc (China Biology Medicine disc) databases and registered websites such as the ICTRP (International Clinical Trial Registration Platform) and clinicaltrials.gov (https://clinicaltrials.gov/) for case-control studies on PCOS and visfatin levels, assessed the quality of the included articles with the Newcastle-Ottawa Scale (NOS scale), and combined the comparison of serum visfatin levels between patients with PCOS and healthy individuals from high-quality studies. RESULTS: 20 research papers were included in the quantitative analysis of this study. The combined analysis showed that obese patients with PCOS had statistically significantly higher visfatin levels than healthy people [MD (mean difference) = 12.94, 95% CI (confidence interval) (6.52-19.37), Z = 3.95, p < 0.0001]. Visfatin levels were higher in non-obese patients with PCOS than in healthy people and are statistically significant [MD = 14.98, 95% CI (5.80-24.16), Z = 3.20, p = 0.001]. Heterogeneity in the combined analysis was not related to study location, the publication year of the literature, source of serum samples, but was influenced by the quality of the literature. After excluding the most influential papers, the combined analysis was conducted again, and the conclusion was consistent with that before the exclusion. The results of Egger's test showed no significant publication bias. CONCLUSIONS: High serum visfatin levels are a natural feature of PCOS and are not associated with obesity; Serum visfatin levels may be a potential marker for the diagnosis of PCOS, but their relationship with PCOS and insulin resistance remains worthy of in-depth investigation.

Polydopamine-coated thalidomide nanocrystals promote DSS-induced murine colitis recovery through Macrophage M2 polarization together with the synergistic anti-inflammatory and anti-angiogenic effects.

High levels of proinflammatory cytokines, macrophage polarization status and immune-mediated angiogenesis play pivotal roles in the pathogenesis of inflammatory bowel disease (IBD). Thalidomide, an anti-inflammatory, immunomodulatory and antiangiogenic agent, is used off-label for treatment of IBD. The therapeutic potential of thalidomide is limited by its poor solubility and side effects associated with its systemic exposure. To address these issues and promote its therapeutic effects on IBD, thalidomide nanocrystals (Thali NCs) were prepared and coated with polydopamine (PDA), a potential macrophage polarization modulator, to form PDA coated Thali NCs (Thali@PDA). Thali@PDA possessed a high drug loading and displayed average particle size of 764.7 ± 50.30 nm. It showed a better anti-colitis effect than bare thalidomide nanocrystals at the same dose of thalidomide. Synergistic effects of polydopamine on anti-inflammatory and anti-angiogenic activities of thalidomide were observed. Furthermore, PDA coating could direct polarization of macrophages towards M2 phenotype, which boosted therapeutic effects of Thali@PDA on IBD. Upon repeated dosing of Thali@PDA for one week, symptoms of IBD in mice were significantly relieved, and histomorphology of the colitis colons were normalized. Key proinflammatory cytokine levels in the inflamed intestines were significantly decreased. Toxicity study also revealed that Thali@PDA is a safe formulation.