Stabilizing the oxidation state of catalysts for effective electrochemical carbon dioxide conversion.

In the electrocatalytic CO2 reduction reaction (CO2RR), metal catalysts with an oxidation state generally demonstrate more favorable catalytic activity and selectivity than their corresponding metallic counterparts. However, the persistence of oxidative metal sites under reductive potentials is challenging since the transition to metallic states inevitably leads to catalytic degradation. Herein, a thorough review of research on oxidation-state stabilization in the CO2RR is presented, starting from fundamental concepts and highlighting the importance of oxidation state stabilization while revealing the relevance of dynamic oxidation states in product distribution. Subsequently, the functional mechanisms of various oxidation-state protection strategies are explained in detail, and in situ detection techniques are discussed. Finally, the prevailing and prospective challenges associated with oxidation-state protection research are discussed, identifying innovative opportunities for mechanistic insights, technology upgrades, and industrial platforms to enable the commercialization of the CO2RR.

Study on the habitat evolution after dam removal in a habitat-alternative tributary of large hydropower station.

The establishment of large hydropower stations in the main stream poses a threat to fish habitats. Selecting suitable tributaries as alternative habitats is a practical measure for ecological environment protection during large hydropower station's construction. The small dams constructed on certain tributaries need to be removed in order to restore river connectivity. The removal of dams will activate hydro-sedimentary dynamics and change the original habitat in terms of topography and hydrodynamics. To explore the evolution of fish habitats following the removal of small dams, a dam-removed reach of a habitat-alternative tributary was selected as the research object, and the model of water-sediment transport and riverbed evolution in strongly disturbed dam-removed reaches and the model of fish habitat suitability evaluation were established. The key parameters calibration and model verification were completed by field monitoring results. The simulation results showed dramatic evolution in the reservoir riverbed in the initial stage after dam removal and during the high discharge period. One year after dam removal, there was a noticeable 4.0 m incision in front of the dam, along with a decrease in channel slope at the dam site from about 4.8% to approximately 1.5%. Downstream of the dam, alterations to the riverbed were mainly concentrated near the dam, and sedimentary bodies with a height of around 2.0 m have formed on the left bank following the high discharge period. The fish habitat in most areas of the dam-removed reach was suitable, except for the downstream high-velocity area. To compare the evolution process of fish habitat under two dam removal periods in wet and dry seasons, two dam removal schemes were implemented in March and June. The results showed that the riverbed evolved more gradually in the March scheme, creating a larger and continuous suitable habitat for fish. Therefore, the March scheme was recommended. By revealing the evolutionary pattern of fish habitat after dam removal, this research provides a reliable model for assessing and restoring habitats in dam-removed reaches, and enjoys significant implications for protecting river ecology in hydropower development reaches.

Strain-Stabilized Metastable Face-Centered Tetragonal Gold Overlayer for Efficient CO2 Electroreduction.

Synthesis of the unconventional phase of noble metal nanocrystals may create new opportunities in exploring intriguing physicochemical properties but remains challenging. In the research field of thin film growth, the interface strain offers a general driving force to stabilize the metastable phase of epitaxial film. Herein we extend this concept to the field of noble metal nanocrystals and report the solution synthesis of metastable face-centered tetragonal Au that has not been discovered before. The successful synthesis relies on the formation of intermetallic AuCu3@Au core-shell structure, where the interface strain stabilizes the metastable fct Au overlayer. Compared with the face-centered cubic Au counterpart, the metastable fct Au shows greatly improved catalytic activity toward CO2 reduction to CO. The density functional theory calculations and spectroscopic studies reveal that the metastable fct Au upshifts the d-band center, which lowers the energy barrier of key intermediate COOH* formation and thus facilitates the reaction kinetics.

Anomalous Size Effect of Pt Ultrathin Nanowires on Oxygen Reduction Reaction.

The classical size effect of Pt particles on oxygen reduction reaction (ORR) suggests that the activity and durability would decrease with reducing the particle size, self-limiting the effectiveness in maximizing the Pt utilization efficiency with the particle-size-reduction strategy. Herein, we discover an anomalous size effect based on Pt nanowires (NWs) with tunable diameters, where the monotonically increasing activity and durability for ORR were observed with decreasing the diameter from 2.4 to 1.1 nm. Our results reveal that the dominant role of increased compressive strain induced by decreasing the diameter of NWs in weakening the adsorption and suppressing the Pt dissolution accounts for this anomalous size effect, where the reduced low-coordinated sites on NWs, the intrinsic structural advantage, is the root. Our findings not only expand the knowledge to the classical size effect but also provide new implications to break through the size limit in the design of Pt-based ORR catalysts.

Intermetallic Compounds: Liquid-Phase Synthesis and Electrocatalytic Applications.

Characterized by long-range atomic ordering, well-defined stoichiometry, and controlled crystal structure, intermetallics have attracted increasing attention in the area of chemical synthesis and catalytic applications. Liquid-phase synthesis of intermetallics has arisen as the promising methodology due to its precise control over size, shape, and resistance toward sintering compared with the traditional metallurgy. This short review tends to provide perspectives on the liquid-phase synthesis of intermetallics in terms of both thermodynamics and methodology, as well as its applications in various catalytic reactions. Specifically, basic thermodynamics and kinetics in the synthesis of intermetallics will be first discussed, followed by discussing the main factors that will affect the formation of intermetallics during synthesis. The application of intermetallics in electrocatalysis will be demonstrated case by case at last. We conclude the review with perspectives on the future developments with respect to both synthesis and catalytic applications.

Misdiagnosis of High-grade Serous Ovarian Cancer With BRCA Mutation as Endometriotic Cyst Due to Its Unique Gross Morphology: A Case Report and Literature Review.

It is believed that high-grade serous ovarian cancer (HGSOC) is a solid or multilocular-solid cancer. Here, we report the case of a 40-yr-old woman with a left ovarian unilocular cyst. Ultrasonography and computed tomographic examination confirmed that the cyst was thin-walled and homogenous in thickness without mural nodules. It was considered to be an endometriotic cyst. Left ovarian cyst excision specimens proved it to be HGSOC after pathologic examination. Therefore, the patient underwent radical surgery for HGSOC. Pathologic examination of radical resection specimens confirmed that the HGSOC was still in FIGO stage IA and no fallopian tube lesion was found. Considering that the patient had a history of breast cancer in both the breasts at a young age, it was hypothesized that the breast cancer susceptibility gene (BRCA) gene may have a germline mutation. Next-generation sequencing confirmed the BRCA1 (c.3770_3771delAG) germline mutation in this patient. Previous studies have reported the special morphological characteristics and growth pattern of HGSOC with BRCA mutation in the advanced stage. Our case demonstrates that HGSOC with the BRCA mutation can also be a unilocular cyst with a thin wall and uniform thickness without a mural nodule, and in the early stage, may have unique gross morphology.

Template-Directed Rapid Synthesis of Pd-Based Ultrathin Porous Intermetallic Nanosheets for Efficient Oxygen Reduction.

Atomically ordered intermetallic nanoparticles exhibit improved catalytic activity and durability relative to random alloy counterparts. However, conventional methods with time-consuming and high-temperature syntheses only have rudimentary capability in controlling the structure of intermetallic nanoparticles, hindering advances of intermetallic nanocatalysts. We report a template-directed strategy for rapid synthesis of Pd-based (PdM, M=Pb, Sn and Cd) ultrathin porous intermetallic nanosheets (UPINs) with tunable sizes. This strategy uses preformed seeds, which act as the template to control the deposition of foreign atoms and the subsequent interatomic diffusion. Using the oxygen reduction reaction (ORR) as a model reaction, the as-synthesized Pd3 Pb UPINs exhibit superior activity, durability, and methanol tolerance. The favored geometrical structure and interatomic interaction between Pd and Pb in Pd3 Pb UPINs are concluded to account for the enhanced ORR performance.

Three-Dimensional NiCo2O4@MnMoO4 Core-Shell Nanoarrays for High-Performance Asymmetric Supercapacitors.

Design of new materials with sophisticated nanostructure has been proven to be an efficient strategy to improve their properties in many applications. Herein, we demonstrate the successful combination of high electron conductive materials of NiCo2O4 with high capacitance materials of MnMoO4 by forming a core-shell nanostructure. The NiCo2O4@MnMoO4 core-shell nanoarrays (CSNAs) electrode possesses high capacitance of 1169 F g-1 (4.24 F cm-2) at a current density of 2.5 mA cm-2, obviously larger than the pristine NiCo2O4 electrode. The asymmetric supercapacitors (ASCs), assembled with NiCo2O4@MnMoO4 CSNAs as binder-free cathode and active carbon (AC) as anode, exhibit high energy density of 15 Wh kg-1 and high power density of 6734 W kg-1. Cycle performance of NiCo2O4@MnMoO4 CSNAs//AC ASCs, conducted at current density of 20 mA cm-2, remain 96.45% of the initial capacitance after 10,000 cycles, demonstrating its excellent long-term cycle stability. Kinetically decoupled analysis reveals that the capacitive capacitance is dominant in the total capacitance of NiCo2O4@MnMoO4 CSNAs electrode, which may be the reason for ultra long cycle stability of ASCs. Our assembled button ASC can easily light up a red LED for 30 min and a green LED for 10 min after being charged for 30 s. The remarkable electrochemical performance of NiCo2O4@MnMoO4 CSNAs//AC ASCs is attributed to its enhanced surface area, abundant electroactive sites, facile electrolyte infiltration into the 3D NiCo2O4@MnMnO4 nanoarrays and fast electron and ion transport path.

Multi-residual 2D network integrating spatial correlation for whole heart segmentation.

Whole heart segmentation (WHS) has significant clinical value for cardiac anatomy, modeling, and analysis of cardiac function. This study aims to address the WHS accuracy on cardiac CT images, as well as the fast inference speed and low graphics processing unit (GPU) memory consumption required by practical clinical applications. Thus, we propose a multi-residual two-dimensional (2D) network integrating spatial correlation for WHS. The network performs slice-by-slice segmentation on three-dimensional cardiac CT images in a 2D encoder-decoder manner. In the network, a convolutional long short-term memory skip connection module is designed to perform spatial correlation feature extraction on the feature maps at different resolutions extracted by the sub-modules of the pre-trained ResNet-based encoder. Moreover, a decoder based on the multi-residual module is designed to analyze the extracted features from the perspectives of multi-scale and channel attention, thereby accurately delineating the various substructures of the heart. The proposed method is verified on a dataset of the multi-modality WHS challenge, an in-house WHS dataset, and a dataset of the abdominal organ segmentation challenge. The dice, Jaccard, average symmetric surface distance, Hausdorff distance, inference time, and maximum GPU memory of the WHS are 0.914, 0.843, 1.066 mm, 15.778 mm, 9.535 s, and 1905 MB, respectively. The proposed network has high accuracy, fast inference speed, minimal GPU memory consumption, strong robustness, and good generalization. It can be deployed to clinical practical applications for WHS and can be effectively extended and applied to other multi-organ segmentation fields. The source code is publicly available at https://github.com/nancy1984yan/MultiResNet-SC.

3D vessel extraction using a scale-adaptive hybrid parametric tracker.

3D vessel extraction has great significance in the diagnosis of vascular diseases. However, accurate extraction of vessels from computed tomography angiography (CTA) data is challenging. For one thing, vessels in different body parts have a wide range of scales and large curvatures; for another, the intensity distributions of vessels in different CTA data vary considerably. Besides, surrounding interfering tissue, like bones or veins with similar intensity, also seriously affects vessel extraction. Considering all the above imaging and structural features of vessels, we propose a new scale-adaptive hybrid parametric tracker (SAHPT) to extract arbitrary vessels of different body parts. First, a geometry-intensity parametric model is constructed to calculate the geometry-intensity response. While geometry parameters are calculated to adapt to the variation in scale, intensity parameters can also be estimated to meet non-uniform intensity distributions. Then, a gradient parametric model is proposed to calculate the gradient response based on a multiscale symmetric normalized gradient filter which can effectively separate the target vessel from surrounding interfering tissue. Last, a hybrid parametric model that combines the geometry-intensity and gradient parametric models is constructed to evaluate how well it fits a local image patch. In the extraction process, a multipath spherical sampling strategy is used to solve the problem of anatomical complexity. We have conducted many quantitative experiments using the synthetic and clinical CTA data, asserting its superior performance compared to traditional or deep learning-based baselines.

Neutrophil extracellular traps contributing to atherosclerosis: From pathophysiology to clinical implications.

Neutrophil extracellular traps (NETs) are network-like structures of chromatin filaments decorated by histones, granules, and cytoplasmic-derived proteins expelled by activated neutrophils under multiple pathogenic conditions. NETs not only capture pathogens in innate immunity but also respond to sterile inflammatory stimuli in atherosclerosis, such as lipoproteins and inflammatory cytokines. Atherosclerosis is a lipid-driven chronic inflammatory disease characterized by the accumulation and transformation of inflammatory cells, and smooth muscle cells in the intimal space. NETs-derived extracellular components possess toxic and proinflammatory properties leading to cellular dysfunction and tissue damage, which may establish a link among lipid metabolism, inflammatory immunity, and atherosclerosis. In this review, we discuss recent advances regarding the role of NETs engaged in the pathogenesis of atherosclerosis, particularly focusing on the interaction with lipids and inflammasomes, crosstalk with smooth muscle cells and inflammatory cells, and the association with aging. We also evaluate the current knowledge on the potential of NETs as biomarkers and therapeutic targets for atherosclerosis and its related diseases in clinical practice.

LIVE-Net: Comprehensive 3D vessel extraction framework in CT angiography.

The extraction of vessels from computed tomography angiography (CTA) is significant in diagnosing and evaluating vascular diseases. However, due to the anatomical complexity, wide intensity distribution, and small volume proportion of vessels, vessel extraction is laborious and time-consuming, and it is easy to lead to error-prone diagnostic results in clinical practice. This study proposes a novel comprehensive vessel extraction framework, called the Local Iterative-based Vessel Extraction Network (LIVE-Net), to achieve 3D vessel segmentation while tracking vessel centerlines. LIVE-Net contains dual dataflow pathways that work alternately: an iterative tracking network and a local segmentation network. The former can generate the fine-grain direction and radius prediction of a vascular patch by using the attention-embedded atrous pyramid network (aAPN), and the latter can achieve 3D vascular lumen segmentation by constructing the multi-order self-attention U-shape network (MOSA-UNet). LIVE-Net is trained and evaluated on two datasets: the MICCAI 2008 Coronary Artery Tracking Challenge (CAT08) dataset and head and neck CTA dataset from the clinic. Experimental results of both tracking and segmentation show that our proposed LIVE-Net exhibits superior performance compared with other state-of-the-art (SOTA) networks. In the CAT08 dataset, the tracked centerlines have an average overlap of 95.2%, overlap until first error of 91.2%, overlap with the clinically relevant vessels of 98.3%, and error distance inside of 0.21 mm. The corresponding tracking overlap metrics in the head and neck CTA dataset are 96.7%, 91.0%, and 99.8%, respectively. In addition, the results of the consistent experiment also show strong clinical correspondence. For the segmentation of bilateral carotid and vertebral arteries, our method can not only achieve better accuracy with an average dice similarity coefficient (DSC) of 90.03%, Intersection over Union (IoU) of 81.97%, and 95% Hausdorff distance (95%HD) of 3.42 mm , but higher efficiency with an average time of 67.25 s , even three times faster compared to some methods applied in full field view. Both the tracking and segmentation results prove the potential clinical utility of our network.

Vessel filtering and segmentation of coronary CT angiographic images.

PURPOSE: Coronary artery segmentation in coronary computed tomography angiography (CTA) images plays a crucial role in diagnosing cardiovascular diseases. However, due to the complexity of coronary CTA images and coronary structure, it is difficult to automatically segment coronary arteries accurately and efficiently from numerous coronary CTA images. METHOD: In this study, an automatic method based on symmetrical radiation filter (SRF) and D-means is presented. The SRF, which is applied to the three orthogonal planes, is designed to filter the suspicious vessel tissue according to the features of gradient changes on vascular boundaries to segment coronary arteries accurately and reduce computational cost. Additionally, the D-means local clustering is proposed to be embedded into vessel segmentation to eliminate noise impact in coronary CTA images. RESULTS: The results of the proposed method were compared against the manual delineations in 210 coronary CTA data sets. The average values of true positive, false positive, Jaccard measure, and Dice coefficient were [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], respectively. Moreover, comparing the delineated data sets and public data sets showed that the proposed method is better than the related methods. CONCLUSION: The experimental results indicate that the proposed method can perform complete, robust, and accurate segmentation of coronary arteries with low computational cost. Therefore, the proposed method is proven effective in vessel segmentation of coronary CTA images without extensive training data and can meet clinical applications.

Abdominal vessel segmentation using vessel model embedded fuzzy C-means and similarity from CT angiography.

The accurate abdominal vessel segmentation of CT angiography (CTA) data is essential for diagnosis and surgical planning. However, accurate abdominal vessel segmentation is a difficult problem since the following challenges: (1) complex abdominal vessel structure containing a wide range size of vessel branches, (2) low contrast of small vessels, and (3) uneven distribution of vessel grayscale. With full consideration of the challenges, we propose an automatic vessel segmentation algorithm. For challenge 1, the algorithm's framework is divided into large and small vessel segmentation and has the following steps. Firstly, a vessel model embedded fuzzy c-means (VMEFCM) method with full consideration of challenge 2 is presented to obtain the initial vessel voxels. Then, considering challenge 3, a large vessel segmentation method based on the initial vessel voxels, similarity, and morphologic is proposed. Finally, a small vessel segmentation method based on spine is described. Extensive analysis is carried out on simulation datasets and 78 CTA datasets. The experimental results indicate that each step of the algorithm achieves the prospective results, and the proposed algorithm is effective and accurate with low computational cost. The dice, sensitivity, Jaccard coefficient, and precision rate were 93.7±2.8%, 93.7±2.8%, 88.2±4.8%, and 94.2±7.5% respectively.

The lumbar region localization using bone anatomy feature graphs.

The automatic localization of the lumbar region is essential for the diagnosis of lumbar diseases, the study of lumbar morphology, and the surgical planning. Although the existing researches have made great progress, it still faces several challenges. First, the various lumbar diseases and pathologies cause different abnormalities in the lumbar shape and appearance. Second, the numbers of lumbar vertebrae are irregular (some people have an additional vertebra L6). To tackle these challenges, we propose a novel lumbar region localization method based on bone anatomy feature graphs. Specifically, a feature graph (called LS) considering the anatomy of the sacrum and the lumbar vertebra is proposed to locate the inferior boundary of L5 or L6. A feature graph (called TL) considering the anatomy of the thoracic vertebra and the lumbar vertebra is proposed to locate the superior boundary of L1. Extensive experimental analysis is performed on a public available dataset xVertSeg and a private dataset which contains 197 CT scans. The localization results show that the proposed method is robust and can be applied to normal scans, scoliosis scans, deformity scans, hyperosteogeny scans, 6 lumbar vertebrae scans and lumbar implant scans. The Dice and Jaccard coefficients are 98.09 ± 0.84% and 96.27 ± 1.62% respectively. Graphical Abstract Lumbar Region Localization Framework.

Stabilizing Pt-Based Electrocatalysts for Oxygen Reduction Reaction: Fundamental Understanding and Design Strategies.

Proton exchange membrane fuel cells (PEMFCs) with high efficiency and nonpollution characteristics have attracted massive attention from both academic and industrial communities due to their irreplaceable roles in building the future sustainable energy system. However, the stability issue of Pt-based catalysts for oxygen reduction reaction (ORR) has become a central constraint to the widespread deployment of the devices relative to the catalytic activity. This review aims to provide comprehensive insights into how to improve the stability of Pt-based catalysts for ORR. First, the basic physical chemistry behind the catalyst degradation, including the fundamental understandings of carbon corrosion, catalyst dissolution, and particle sintering, is highlighted. After a discussion of advanced characterization techniques for the catalyst degradation, the design strategies for improving the stability of Pt-based catalysts are summarized. Finally, further insights into the remaining challenges and future research directions are also provided.

Association between postprandial lipoprotein subclasses and Framingham cardiovascular disease risk stratification.

OBJECTIVE: To determine the ability of postprandial lipoprotein subclass concentrations to stratify patients with respect to their risk for cardiovascular disease (CVD). METHODS: Using the Framingham cardiovascular disease risk score (FRS) algorithm, a total of 112 consecutive patients referred for community health screening were stratified into two groups: (a) low-risk (FRS < 10%) and (b) intermediate/high-risk (FRS ≥ 10%). Serum lipoprotein subclass concentrations were determined by Vertical Auto Profile (VAP-II). RESULTS: Fasting and postprandial levels of LDL4, HDL2, VLDL1 + 2, VLDL3, and RLP, as well as fasting levels of ApoB and postprandial levels of LDL3 and IDL1, were significantly different in the intermediate/high risk FRS group vs. the low-risk group (P < 0.05). Correlations between Framingham CVD risk and LDL3, LDL4, IDL1, VLDL1 + 2, VLDL3, RLP, and ApoB were positive while negative for HDL2 in both the fasting and postprandial states. Intermediate/high risk for CVD was shown to be significantly associated with both fasting and postprandial levels of VLDL1 + 2 and RLP, as well as with postprandial LDL4 and VLDL3, as determined using forward conditional logistic regression analysis. Postprandial levels of VLDL1 + 2 were better at identifying patients in the intermediate/high-risk FRS group than fasting levels, although the differences were not significant due to overlapping reference intervals. In addition, the association between RLP and VLDL subclasses relative to Framingham CVD risk increased significantly in the postprandial state (ΔR2 = 0.023; ΔF = 7.178; ΔP = 0.025) but not in the fasting state. CONCLUSIONS: The use of postprandial lipoprotein subclass concentrations is not inferior to the use of fasting levels in identifying intermediate/high-risk FRS individuals. In addition, changes in RLP and VLDL subclass concentrations in fasting vs. postprandial states may reveal lipid metabolic mechanisms associated with CVD.

microRNA-204-5p Participates in Atherosclerosis Via Targeting MMP-9.

The aim of the present study was to investigate the role and mechanism of microRNA-204-5p (miR-204-5p) in atherosclerosis (AS)-related abnormal human vascular smooth muscle cells (hVSMCs) function. Firstly, we analyzed the expression of miR-204-5p and found that the miR-204-5p expression level was clearly downregulated in atherosclerotic plaque tissues and blood samples compared to the normal controls. Then, matrix metallopeptidase-9 (MMP-9) was predicted to be the potential target of miR-204-5p by TargetScan and this prediction was confirmed by luciferase assays. Besides, we observed that miR-204-5p could negatively regulate the expression of MMP-9 in hVSMCs. Subsequently, Thiazolyl Blue Tetrazolium Bromide (MTT) assay, transwell assay and flow cytometry were performed to detect the proliferation, migration and apoptosis of hVSMCs. Down-expression of miR-204-5p led to the promotion of proliferation and migration accompanied with the suppression of apoptosis in hVSMCs, and these effects were reversed by MMP-9-siRNA. In addition, overexpressed miR-204-5p could inhibit hVSMC proliferation and migration and promote the apoptosis of hVSMCs. However, the effects were also abrogated by overexpressed MMP-9. Together, our findings showed that miR-204-5p plays an important role in the growth and migration of hVSMCs by targeting MMP-9, which might be a novel biomarker and promising therapeutic target for AS.

Applications of Metal Nanocrystals with Twin Defects in Electrocatalysis.

Electrocatalytic energy conversion is one of the most promising pathways to develop clean and renewable energy technologies, and the development of high-performance electrocatalysts to improve the energy conversion efficiency is of paramount importance. Metal nanocrystals with twin defects possess unique features, including lattice strain and high density of low-coordinated atoms at the twin boundary, endowing them with excellent catalytic performance in various electrocatalytic reactions. Herein, we briefly summarize recent advances in the synthesis of metal nanocrystals with various twin structures, recent breakthroughs related to electrocatalytic applications of twin metal nanocrystals are also overviewed. Finally, the major challenges and perspectives for future development of twin metal nanocrystals in electrochemical applications are proposed.

Circulating CD14+HLA-DR-/low Myeloid-Derived Suppressor Cells as Potential Biomarkers for the Identification of Psoriasis TCM Blood-Heat Syndrome and Blood-Stasis Syndrome.

Psoriasis is a chronic autoimmune disease. Identification of the biomarkers responsible for Traditional Chinese Medicine (TCM) syndromes of psoriasis can help researchers recognize the different aspects of psoriasis and find novel therapeutic targets for the treatment of psoriasis. The current study investigated the levels of circulating Mo-MDSCs and Mo-MDSC-associated immune factors in the peripheral blood of psoriasis patients with different TCM syndromes. We found that the frequency of Mo-MDSCs (CD14+HLA-DR-/low cells) among CD14+ cells from plaque psoriasis patients with blood-stasis (BS) syndrome was significantly increased when compared with healthy controls (p < 0.001) and blood-heat (BH) syndrome group (p < 0.001), respectively. However, serum IL-2, IL-4, IL-6, IL-10, IL-17A, TNF-α, IFN-γ, iNOS, Arg-1, and NO concentration showed no statistically significant difference between healthy controls and psoriasis patients as well as no significant difference between the BH and BS syndrome groups. Compared with healthy controls, the mRNA expression of Arg-1, TNF-α, ROR-γ, and PD-L1 was increased, while the mRNA expression of PD-1 and IL-10 was decreased in PBMCs from psoriasis patients. Moreover, the mRNA expression of TNF-α and FOXP3 in PBMCs showed a pronounced statistical difference between the psoriatic BH syndrome group and the BS syndrome group. Therefore, we provide evidence that the percentage of CD14+HLA-DR-/low MDSC/ CD14+ cells and TNF-α and Foxp3 mRNA expression levels in PBMCs are potential biomarkers for distinguishing TCM BH syndrome and BS syndrome.