The switch triggering the invasion process: Lipid metabolism in the metastasis of hepatocellular carcinoma.

ABSTRACT: In humans, the liver is a central metabolic organ with a complex and unique histological microenvironment. Hepatocellular carcinoma (HCC), which is a highly aggressive disease with a poor prognosis, accounts for most cases of primary liver cancer. As an emerging hallmark of cancers, metabolic reprogramming acts as a runaway mechanism that disrupts homeostasis of the affected organs, including the liver. Specifically, rewiring of the liver metabolic microenvironment, including lipid metabolism, is driven by HCC cells, propelling the phenotypes of HCC cells, including dissemination, invasion, and even metastasis in return. The resulting formation of this vicious loop facilitates various malignant behaviors of HCC further. However, few articles have comprehensively summarized lipid reprogramming in HCC metastasis. Here, we have reviewed the general situation of the liver microenvironment and the physiological lipid metabolism in the liver, and highlighted the effects of different aspects of lipid metabolism on HCC metastasis to explore the underlying mechanisms. In addition, we have recapitulated promising therapeutic strategies targeting lipid metabolism and the effects of lipid metabolic reprogramming on the efficacy of HCC systematical therapy, aiming to offer new perspectives for targeted therapy.

Predictive modeling of co-infection in lupus nephritis using multiple machine learning algorithms.

This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and use machine learning (ML) methods to establish an effective algorithm for predicting co-infection in LN. This study included 111 non-infected LN patients, 72 infected LN patients, and 206 healthy controls (HCs). Patient information, infection characteristics, medication, and laboratory indexes were recorded. Eight ML methods were compared to establish a model through a training group and verify the results in a test group. We trained the ML models, including Logistic Regression, Decision Tree, K-Nearest Neighbors, Support Vector Machine, Multi-Layer Perceptron, Random Forest, Ada boost, Extreme Gradient Boosting (XGB), and further evaluated potential predictors of infection. Infected LN patients had significantly decreased levels of T, B, helper T, suppressor T, and natural killer cells compared to non-infected LN patients and HCs. The number of regulatory T cells (Tregs) in LN patients was significantly lower than in HCs, with infected patients having the lowest Tregs count. Among the ML algorithms, XGB demonstrated the highest accuracy and precision for predicting LN infections. The innate and adaptive immune systems are disrupted in LN patients, and monitoring lymphocyte subsets can help prevent and treat infections. The XGB algorithm was recommended for predicting co-infection in LN.

Cumulative sum learning curve analysis of tubularized incised plate repair for hypospadias: a study of a single surgeon with a single surgical procedure.

Purpose: To ascertain the quantity of instances by which a single surgeon achieves competency and proficiency in using tubularized incised plate (TIP) technique for the repair of distal and mid-shaft hypospadias using the cumulative sum (CUSUM) analysis. Methods: We retrospectively evaluated patients with distal and mid-shaft hypospadias who were treated by a single surgeon between 2015 and 2021, using a single primary TIP technique with a de-epithelialized Byars flap. Data including type of hypospadias, age at surgery, curvature, operation time (OT), length of the reconstructed urethra, and postoperative outcomes were collected and assessed. CUSUM was used to assess the trends in OT and complication rate (CR) in order to generate the learning curve. The evolution of OT and CR can be divided into three phases: learning, competence, and proficiency. Results: CUSUM identified three phases in the learning curves of all TIP repairs. The median OT decreased from 135 min [interquartile range (IQR) = 125-155] to 92 min (IQR = 80-100) (P < 0.001), CR decreased from 28 (28%) to 8 (5.3%) (P < 0.001), and reoperations decreased from 15 (15.2%) to 4 (2.6%) (P < 0.001). According to the CUSUM learning curve, technical competency plateaued after the 99th case, and both OT and CR entered a significantly declining proficiency phase after the 231st case. Further, when the neourethral length exceeded the total average, total complications, urethrocutaneous fistula, and reoperations increased (P = 0.013, P = 0.006, and P = 0.028, respectively). Conclusions: Our study suggests that surgeons performing TIP repair may reach technical competency and achieve proficiency after operating on 99,231 cases, respectively. Moreover, the longer the neourethral length, the higher is the CR.

Efficient Extraction and Analysis of Nanoplastics by Ionic Liquid-Assisted Cloud-Point Extraction Coupled with Electromagnetic Heating Pyrolysis Mass Spectrometry.

Nanoplastics have attracted much attention due to their potential hazards. However, analysis of nanoplastics remains challenging. In this study, ionic liquid-assisted cloud-point extraction (IL-assisted CPE) was developed to enrich nanoplastics in the aqueous environment and further coupled with electromagnetic heating pyrolysis mass spectrometry. The use of trace ILs improves the extraction efficiency of CPE for nanoplastics. The effects of ILs (types, contents), nanoplastic properties (type, size), and environmental factors (aging time, humic acid content) were systematically investigated to evaluate the applicability. The limits of detection of poly(methyl methacrylate) (PMMA) and polystyrene (PS) were determined to be 1.78 and 2.67 µg/L, respectively. Real environmental samples including lake water, rainwater, and influent and effluent from wastewater treatment plant were analyzed with good accuracy (79.58-116.87%) and satisfactory precision (RSD ≤ 11.99%). A possible mechanism for ILs being absorbed into the ordered surfactant micellar and generating larger micelles to synergically enclose hydrophobic nanoplastics was proposed. This work provides a simple and efficient approach to the extraction and analysis of nanoplastics in aqueous environments.

Vertical migration behavior simulation and prediction of Pb and Cd in co-contaminated soil around Pb-Zn smelting slag site.

Heavy metal migration in soil poses a serious threat to the soil and groundwater. Understanding the migration pattern of heavy metals (HMs) under different factors could provide a more reasonable position for pollution evaluation and targetoriented treatment of soil heavy metal. In this study, the migration behavior of Pb and Cd in co-contaminated soil under different pH and ionic strength (NaCl concentration) was simulated using convective dispersion equation (CDE). We predicted the migration trends of Pb and Cd in soils after 5, 10, and 20 years via PHREEQC. The results showed that the migration time of Cd in the soil column experiment was about 60 days faster than that of Pb, and the migration trend was much steeper. The CDE was proved to describe the migration behavior of Pb and Cd (R2 > 0.75) in soil. The predicted results showed that Cd migrated to 15-20 cm of soil within 7 years and Pb stayed mainly in the top 0-6 cm of soil within 5 years as the duration of irrigation increased. Overall, our study is expected to provide new insight into the migration of heavy metal in soil ecosystems and guidance for reducing risk of heavy metal in the environment.

Advances in researches on long coronavirus disease in children: a narrative review.

Background and Objective: In the context of the global pandemic of coronavirus disease 2019 (COVID-19), more than 700 million infections and millions of deaths have occurred in countries around the world. Currently, two main sequelae of this disease are considered to occur in children, namely, multi-system inflammatory syndrome in children and long COVID. Among these two, the incidence of long COVID is higher and its impact on the population is more extensive, which is the focus of us. However, due to the lack of relevant studies and the limitations of most studies, the studies on sequelae of COVID-19 infection lag behind those of adults, but they have begun to attract the attention of some clinicians and researchers. We aim to summarize the current knowledge of long COVID in children, helping pediatricians and researchers to better understand this disease and providing guidance on research and clinical treatment of it. Methods: We reviewed all the studies on "long COVID", pediatric, children, adolescent, post-COVID syndrome in PubMed published after 2019. Key Content and Findings: This review summarizes the latest researches on epidemiology, pathogenesis, clinical manifestations, prevention and treatment of long COVID in children. Based on the existing research data, we summarized and analyzed the characteristics of long COVID in children, discovering the means to decipher the diagnosis of COVID-19 in children and some potential therapeutic treatments. Conclusions: We aim to summarize existing research on long COVID in children and help pediatricians and government agencies quickly understand the disease so that it can be used for clinical diagnosis, treatment and prevention in the population. In addition, providing a research basis for further researches on the cellular and even molecular level to explain the occurrence and development of diseases, and has a guiding role for future research direction.

Augmenting regulatory T cells: new therapeutic strategy for rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune condition marked by inflammation of the joints, degradation of the articular cartilage, and bone resorption. Recent studies found the absolute and relative decreases in circulating regulatory T cells (Tregs) in RA patients. Tregs are a unique type of cells exhibiting immunosuppressive functions, known for expressing the Foxp3 gene. They are instrumental in maintaining immunological tolerance and preventing autoimmunity. Increasing the absolute number and/or enhancing the function of Tregs are effective strategies for treating RA. This article reviews the studies on the mechanisms and targeted therapies related to Tregs in RA, with a view to provide better ideas for the treatment of RA.

The nematode effector calreticulin competes with the high mobility group protein OsHMGB1 for binding to the rice calmodulin-like protein OsCML31 to enhance rice susceptibility to Meloidogyne graminicola.

The root-knot nematode Meloidogyne graminicola secretes effectors into rice tissues to modulate host immunity. Here, we characterised MgCRT1, a calreticulin protein of M. graminicola, and identified its target in the plant. In situ hybridisation showed MgCRT1 mRNA accumulating in the subventral oesophageal gland in J2 nematodes. Immunolocalization indicated MgCRT1 localises in the giant cells during parasitism. Host-induced gene silencing of MgCRT1 reduced the infection ability of M. graminicola, while over-expressing MgCRT1 enhanced rice susceptibility to M. graminicola. A yeast two-hybrid approach identified the calmodulin-like protein OsCML31 as an interactor of MgCRT1. OsCML31 interacts with the high mobility group protein OsHMGB1 which is a conserved DNA binding protein. Knockout of OsCML31 or overexpression of OsHMGB1 in rice results in enhanced susceptibility to M. graminicola. In contrast, overexpression of OsCML31 or knockout of OsHMGB1 in rice decreases susceptibility to M. graminicola. The GST-pulldown and luciferase complementation imaging assay showed that MgCRT1 decreases the interaction of OsCML31 and OsHMGB1 in a competitive manner. In conclusion, when M. graminicola infects rice and secretes MgCRT1 into rice, MgCRT1 interacts with OsCML31 and decreases the association of OsCML31 with OsHMGB1, resulting in the release of OsHMGB1 to enhance rice susceptibility.

Transcription factor BACH1 in cancer: roles, mechanisms, and prospects for targeted therapy.

Transcription factor BTB domain and CNC homology 1 (BACH1) belongs to the Cap 'n' Collar and basic region Leucine Zipper (CNC-bZIP) family. BACH1 is widely expressed in mammalian tissues, where it regulates epigenetic modifications, heme homeostasis, and oxidative stress. Additionally, it is involved in immune system development. More importantly, BACH1 is highly expressed in and plays a key role in numerous malignant tumors, affecting cellular metabolism, tumor invasion and metastasis, proliferation, different cell death pathways, drug resistance, and the tumor microenvironment. However, few articles systematically summarized the roles of BACH1 in cancer. This review aims to highlight the research status of BACH1 in malignant tumor behaviors, and summarize its role in immune regulation in cancer. Moreover, this review focuses on the potential of BACH1 as a novel therapeutic target and prognostic biomarker. Notably, the mechanisms underlying the roles of BACH1 in ferroptosis, oxidative stress and tumor microenvironment remain to be explored. BACH1 has a dual impact on cancer, which affects the accuracy and efficiency of targeted drug delivery. Finally, the promising directions of future BACH1 research are prospected. A systematical and clear understanding of BACH1 would undoubtedly take us one step closer to facilitating its translation from basic research into the clinic.

SOX on tumors, a comfort or a constraint?

The sex-determining region Y (SRY)-related high-mobility group (HMG) box (SOX) family, composed of 20 transcription factors, is a conserved family with a highly homologous HMG domain. Due to their crucial role in determining cell fate, the dysregulation of SOX family members is closely associated with tumorigenesis, including tumor invasion, metastasis, proliferation, apoptosis, epithelial-mesenchymal transition, stemness and drug resistance. Despite considerable research to investigate the mechanisms and functions of the SOX family, confusion remains regarding aspects such as the role of the SOX family in tumor immune microenvironment (TIME) and contradictory impacts the SOX family exerts on tumors. This review summarizes the physiological function of the SOX family and their multiple roles in tumors, with a focus on the relationship between the SOX family and TIME, aiming to propose their potential role in cancer and promising methods for treatment.

Detection of nanoplastics released from consumer plastic food containers by electromagnetic heating pyrolysis mass spectrometry.

Nanoplastics released from consumer plastic food containers are emerging environmental pollutants and directly ingested as part of the diet. However, quantification methods for nanoplastics are still lacking. Herein, a rapid identification and mass quantification approach was developed for nanoplastics analysis by combining electromagnetic heating with pyrolysis mass spectrometry (Eh-Py-MS). The pyrolysis products directly entered into the MS, which omits the gas phase separation process and shortens the detection time. A compact pyrolysis chamber was used and this increased the sample transfer efficiency and lowered power requirement. The operational parameters were systematically examined. The influence of nanoplastic size, additive, humic acid, and aging on detection was investigated, and it was concluded that environmental factors (humic acid, aging) and plastic properties (size, additives) did not influence the detection. The developed chamber showed that the limit of detection of polystyrene (PS) nanoplastics was 15.72 ng. Several typical food packages were demonstrated with satisfactory recovery rates (87.5-110%) and precision (RSD ≤11.36%). These results suggested that the consumer plastic food containers are a significant source of direct exposure to nanoplastics in humans from the environment.

Comprehensive transcriptomic analysis and machine learning reveal unique gene expression profiles in patients with immune-mediated necrotizing myopathy.

BACKGROUND: Immune-mediated necrotizing myopathy (IMNM) is an autoimmune myopathy characterized by severe proximal weakness and muscle fiber necrosis, yet its pathogenesis remains unclear. So far, there are few bioinformatics studies on underlying pathogenic genes and infiltrating immune cell profiles of IMNM. Therefore, we aimed to characterize differentially expressed genes (DEGs) and infiltrating cells in IMNM muscle biopsy specimens, which may be useful for elucidating the pathogenesis of IMNM. METHODS: Three datasets (GSE39454, GSE48280 and GSE128470) of gene expression profiling related to IMNM were obtained from the Gene Expression Omnibus database. Data were normalized, and DEG analysis was performed using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed using clusterProfiler. The CIBERSORT algorithm was performed to identify infiltrating cells. Machine learning algorithm and gene set enrichment analysis (GSEA) were performed to find distinctive gene signatures and the underlying signaling pathways of IMNM. RESULTS: DEG analysis identified upregulated and downregulated in IMNM muscle compared to the gene expression levels of other groups. GO and KEGG analysis showed that the pathogenesis of IMNM was notable for the under-representation of pathways that were important in dermatomyositis and inclusion body myositis. Three immune cells (M2 macrophages, resting dendritic cells and resting natural killer cells) with differential infiltration and five key genes (NDUFAF7, POLR2J, CD99, ARF5 and SKAP2) in patients with IMNM were identified through the CIBERSORT and machine learning algorithm. The GSEA results revealed that the key genes were remarkably enriched in diverse immunological and muscle metabolism-related pathways. CONCLUSIONS: We comprehensively explored immunological landscape of IMNM, which is indicative for the research of IMNM pathogenesis.

Nickel/photoredox dual catalyzed arylalkylation of nonactivated alkenes.

Alkene dicarbofunctionalization is an efficient strategy and operation-economic fashion for introducing complexity in molecules. A nickel/photoredox dual catalyzed arylalkylation of nonactivated alkenes for the simultaneous construction of one C(sp3)-C(sp3) bond and one C(sp3)-C(sp2) bond has been developed. The mild catalytic method provided valuable indanethylamine derivatives with wide substrate scope and good functional group compatibility. An enantioselective dicarbofunctionalization was also achieved with pyridine-oxazoline as a ligand. The efficiency of metallaphotoredox dicarbofunctionalization was demonstrated for the concise synthesis of pharmaceutically active compounds.

High-order framework nucleic acid for targeted-delivery of antisense peptide nucleic acids to overcome drug resistance.

A sophisticated high-order framework nucleic acid (FNA) was engineered for the targeted delivery and responsive release of environment tolerant antisense peptide nucleic acids (asPNAs). The dendritic FNA-asPNAs system was constructed via simple one-pot modular assembly and demonstrated a good synergistic effect with chemotherapy on drug resistant cancer cells.

Rapid Estimation of Soil Pb Concentration Based on Spectral Feature Screening and Multi-Strategy Spectral Fusion.

Traditional methods for obtaining soil heavy metal content are expensive, inefficient, and limited in monitoring range. In order to meet the needs of soil environmental quality evaluation and health status assessment, visible near-infrared spectroscopy and XRF spectroscopy for monitoring heavy metal content in soil have attracted much attention, because of their rapid, nondestructive, economical, and environmentally friendly features. The use of either of these spectra alone cannot meet the accuracy requirements of traditional measurements, while the synergistic use of the two spectra can further improve the accuracy of monitoring heavy metal lead content in soil. Therefore, this study applied various spectral transformations and preprocessing to vis-NIR and XRF spectra; used the whale optimization algorithm (WOA) and competitive adaptive re-weighted sampling (CARS) algorithms to identify feature spectra; designed a combination variable model (CVM) based on multi-layer spectral data fusion, which improved the spectral preprocessing and spectral feature screening process to increase the efficiency of spectral fusion; and established a quantitative model for soil Pb concentration using partial least squares regression (PLSR). The estimation performance of three spectral fusion strategies, CVM, outer-product analysis (OPA), and Granger-Ramanathan averaging (GRA), was discussed. The results showed that the accuracy and efficiency of the CARS algorithm in the fused spectra estimation model were superior to those of the WOA algorithm, with an average coefficient of determination (R2) value of 0.9226 and an average root mean square error (RMSE) of 0.1984. The accuracy of the estimation models established, based on the different spectral types, to predict the Pb content of the soil was ranked as follows: the CVM model > the XRF spectral model > the vis-NIR spectral model. Within the CVM fusion strategy, the estimation model based on CARS and PLSR (CARS_D1+D2) performed the best, with R2 and RMSE values of 0.9546 and 0.2035, respectively. Among the three spectral fusion strategies, CVM had the highest accuracy, OPA had the smallest errors, and GRA showed a more balanced performance. This study provides technical means for on-site rapid estimation of Pb content based on multi-source spectral fusion and lays the foundation for subsequent research on dynamic, real-time, and large-scale quantitative monitoring of soil heavy metal pollution using high-spectral remote sensing images.

Curvature geometry in 2D materials.

The two-dimensional (2D) material family can be regarded as the extreme externalization form of the matter in the planar 2D space. These atomically thin materials have abundant curvature structures, which will significantly affect their atomic configurations and physicochemical properties. Curvature engineering offers a new tuning freedom beyond the thoroughly studied layer number, grain boundaries, stacking order, etc. The precise control of the curvature geometry in 2D materials can redefine this material family. Special attention will be given to this emerging field and highlight possible future directions. With the step-by-step achievement in understanding the curvature engineering effect in 2D materials and establishing reliable delicate curvature controlling strategies, a brand-new era of 2D materials research could be developed.

Contamination characteristics and source analysis of potentially toxic elements in dustfall-soil-crop systems near non-ferrous mining areas of Yunnan, southwestern China.

Potentially toxic elements (PTEs) in the dustfall-soil-crop system pose a serious threat to the ecological environment and agricultural production. However, there is still a knowledge gap in terms of better understanding the distinctive sources of PTEs by integrating various models and technologies. In this study, we comprehensively investigated the concentrations, distribution, and sources of seven PTEs in a dustfall-soil-crop system (424 samples in total) near a typical non-ferrous mining area, using absolute principal component score/multiple linear regression (APCS/MLR) combined with X-ray diffraction (XRD) and microscopy techniques. Our results showed that the mean values of As, Cd, Cr, Cu, Ni, Pb, and Zn in the soils were 211, 14, 105, 91, 65, 232, and 325 mg/kg, respectively. These values were significantly higher than the background soil values in Yunnan. Except for Ni and Cr, all elements in the soil were significantly higher than the screening values of agricultural lands in China. The spatial distribution of PTE concentrations was similar among the three media. The ACPS/MLR, XRD, and microscopy analyses further indicated that soil PTEs mainly originated from industrial activities (37 %), vehicle emissions and agricultural activities (29 %), respectively. Dustfall PTEs mainly originated from vehicle emissions and industrial activities, accounting for 40 % and 37 %, respectively. Crop PTEs mainly originated from vehicle emissions and soil (57 %), and agricultural activities (11 %), respectively. PTEs seriously threaten the safety of agricultural products and the ecological environment once they settle from the atmosphere to soil and crop leaves, further accumulate in crops, and spread through the food chain. Therefore, our study provides scientific evidence for government regulators to control PTE pollution and reduce their environmental risks in dustfall-soil-crop systems.

Care patterns and Traditional Chinese Medicine constitution as factors of depression and anxiety in patients with systemic sclerosis: A cross-sectional study during the COVID-19 pandemic.

Objective: Care patterns and Traditional Chinese Medicine (TCM) constitution affects the emotion and health of patients with systemic sclerosis (SSc) while the prevalence of COVID-19 may aggravate such patients' emotion and health. We investigated the depression and anxiety levels of patients with SSc during the pandemic to identify the correlation between care patterns, TCM constitution, and patients' emotion. Materials and methods: This was a cross-sectional study. Patients with SSc and healthy individuals were surveyed using the patient health questionnaire-9, generalized anxiety disorder-7, and constitution in Chinese medicine questionnaire and a modified care pattern questionnaire. Factors correlated with depression and anxiety were screened using univariate and multivariate logistic regression analyses. Results: A total of 273 patients with SSc and 111 healthy individuals were included in the analysis. The proportion of patients with SSc who were depressed was 74.36%, who had anxiety was 51.65%, and who experienced disease progression during the pandemic was 36.99%. The proportion of income reduction in the online group (56.19%) was higher than that in the hospital group (33.33%) (P = 0.001). Qi-deficiency [adjusted odds ratio (OR) = 2.250] and Qi-stagnation (adjusted OR = 3.824) constitutions were significantly associated with depression. Remote work during the outbreak (adjusted OR = 1.920), decrease in income (adjusted OR = 3.556), and disease progression (P = 0.030) were associated with the occurrence of depression. Conclusion: Chinese patients with SSc have a high prevalence of depression and anxiety. The COVID-19 pandemic has changed the care patterns of Chinese patients with SSc, and work, income, disease progression, and change of medications were correlates of depression or anxiety in patients with SSc. Qi-stagnation and Qi-deficiency constitutions were associated with depression, and Qi-stagnation constitution was associated with anxiety in patients with SSc. Trial registration: http://www.chictr.org.cn/showproj.aspx?proj=62301, identifier ChiCTR2000038796.

Distribution and risk assessment of microplastics in Liujiaxia Reservoir on the upper Yellow River.

Microplastics (MPSs) distribution in global freshwater systems is extensively reported, but the distribution of MPSs in reservoirs of the Yellow River has rarely been studied. To fill in this gap, we systematically investigated the distribution of MPSs in surface water and bank sediments gleaned from Liujiaxia Reservoir of the upper Yellow River for the first time and conducted an ecological risk assessment in succession in this work. The results showed that the main polymer types of MPSs in the surface water and bank sediments of Liujiaxia Reservoir were polyethylene terephthalate (PET), polystyrene (PS), and polypropylene (PP), and the abundance of MPSs in the reservoir surface water and bank sediments ranged from 4.48 to 12.09 item/L and 447.27 to 1543.80 item/kg (dry weight), respectively. Further physical morphology analysis of MPSs in the samples revealed that MPSs in the surface water and bank sediments of Liujiaxia Reservoir were predominantly fibrous with small particle sizes (<1 mm), and there was abundant color, mainly exhibiting transparent, black, and blue. The results of the MPS pollution load index (PLI>1) and the hazard ranking of MPSs (HZone = 10.20 for surface water and HZone = 14.06 for bank sediments) yielded a hazard class II for MPS pollution in Liujiaxia Reservoir, the combined pollution risk index (PRIZone = 17.05 for surface water and PRIZone = 31.25 for bank sediments) stated clearly the potential ecological risk in the Liujiaxia Reservoir. Briefly, this study supplemented and enriched the data on the distribution of MPSs in the reservoirs of the Yellow River basin, and provide a benchmark for future pollution control and management in the reservoir area.

Risk factors analysis and risk assessment model construction of systemic lupus erythematosus patients with infection.

OBJECTIVE: To analyze the characteristics of peripheral blood lymphocyte subsets in systemic lupus erythematosus (SLE) patients with infection and non-infection group. Explore the risk factors of infection in SLE patients and establish a risk matrix model to predict the occurrence of co-infection. METHODS: total of 333 SLE patients without infection, 163 patients suffering from infection, and 132 healthy controls (HCs) were recruited. General clinical data and disease activity indicators were collected. The levels of total T, B, CD4+T, CD8+T, NK, Th1, Th2, Th17, and Treg cells in peripheral blood of HCs, SLE patients (including infected and non-infected group) were analyzed by flow cytometry. The risk assessment model was constructed, and the receiver operating characteristic curve was drawn. 39 SLE patients with infection and 20 patients without infection were randomly selected to evaluate the predictive power of the regression model. RESULTS: The levels of T, B, CD4+T, CD8+T, and NK cells in the infected patients were significantly decreased when compared with that of both non-infected patients and HCs (p < .05). The non-infected patients had a higher level of Th17 than that of HCs (p < . 05), but the absolute numbers of Th17 in infected patients was the lowest among the three groups (p < .001). The number of Treg cells in SLE patients was significantly lower than that of HCs (p < .01), and the infected patients had the fewest Treg cells among all these groups (p < . 05). A risk assessment model for SLE with infection was established, p = 1/(1-e-y), Y = 1.763-0.004 × Absolute number of CD4 + T cells-0.005 × Absolute number of NK cells -0.005 × Platelet count(×1012/L) + 1.033 × Absolute number of lymphocytes (×109/L) + 0.023 × C-reactive protein (mg/dL), whose predictive sensitivity is 77.5%, and specificity is 78.3%. CONCLUSION: The new risk assessment model exhibits good predictive ability to assess co-infection risk in SLE patients. T cells, NK cells, and CD4 + T cells along with other parameters help in differentiating Lupus with infection from Lupus alone.