Exploring the expression and diagnostic value of CD177 + neutrophils in tuberculosis patients

Exploring the expression and diagnostic value of CD177 + neutrophils in tuberculosis patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring the expression and diagnostic value of CD177 + neutrophils in tuberculosis patients Xue Li, Zaichuan Lin, Rigu Su, Jun Liu, Qing Luo, Zikun Huang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7809533/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Granulocyte subsets, such as normal -density granulocytes(NDG) and low-density granulocytes(LDG), play an important role in the pathogenesis of tuberculosis (TB). CD177 + neutrophils were up-regulated during inflammation and tumour. H owever, the role of CD177 of neutrophils in TB patients remain elusive. This study aimed to explore the expression of CD177 + neutrophils in TB patients and assess the correlation between CD177 and clinical characteristics to determine the expression and diagnostic value of CD177 + neutrophils of tuberculosis patients. Methods The expression of CD177 of LDG and NDG were confirmed by flow cytometry in 42 TB patients and 26 healthy controls. The levels of markers related to granulocyte activation(CD66b) and immunosuppression programmed death receptor 1 ( PD1) in CD177 + LDG and CD177 + NDG were compared in 27 TB patients. The levels of IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, TNF-α, and IFN-γ were measured with cytokine profiling kits. Correlations with clinical characteristics, inflammatory markers and cytokines as well as receiver operating characteristic (ROC) curve analysis were determined. Results Flow cytometry analysis confirmed the elevated CD177 + LDG and low CD177 + NDG expression in TB patients compared with healthy controls. CD177 + LDG was characterized by high CD66b and low PD-1 expression and was significant ly correlat ed with CD66b and culture filtrate protein 10 spot-forming cells (CFP-10 SFC), and CD177 + NDG is associated with PD1. In addition, the percentage of CD177 + LDG, the percentage of PD1 of CD177 + LDG, and MFI of PD1 of CD177 + LDG were all significantly increased in the EPTB group compared to the PTB group. T he percentage of CD177 + NDG showed 90.00% sensitivity and 59.26% specificity with an AUC of 0.748 in distinguishing between patients with TB and HC , followed by the MFI of CD177 of LDG. Notably, MFI of PD1 on CD177 + LDG harbored the highest AUCs to differentiate EPTB and PTB with 70.00% sensitivity and 88.24% specificity(AUC = 0.818 ). These findings underscore the role of CD177 in granulocyte subsets of TB. Tuberculosis neutrophils LDG CD177 diagnostic Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Mycobacterium tuberculosis (Mtb) is an obligate aerobic and non-motile pathogenic bacterium primarily transmitted through respiratory droplets. The disease tuberculosis (TB), which is instigated by Mtb, continues to pose a significant challenge to global health. According to the World Health Organization's 2023 epidemiological report [ 1 ] , there were approximately 10.8 million newly reported cases of TB and 1.25 million deaths linked to this disease. It is noteworthy that TB has recently overtaken COVID-19, becoming the foremost cause of mortality among infectious agents globally, despite the ongoing advancements in treatment options [ 2 ] . The pathophysiological mechanisms underlying tuberculosis are intricate, involving the host's immune response, the biological properties of the bacterium, and various environmental influences [ 3 ] . Neutrophils are crucial in the processes of engulfing and eradicating pathogens during the initial phases of infection, employing mechanisms such as phagocytosis, oxidative burst, and the generation of neutrophil extracellular traps (NETs) [ 4 , 5 ] . In patients suffering from pulmonary tuberculosis (PTB), the extent of tissue damage in the lungs is significantly associated with both the quantity and the functional status of neutrophils [ 6 ] . Normal-density granulocytes (NDG) are involved in the direct destruction of Mycobacterium tuberculosis (MTB) and play a regulatory role in the immune response by releasing cytokines and chemokines. These neutrophils can produce various cytokines, including interleukin 6 (IL-6), interleukin-1 beta (IL-1β), and interferon-γ (IFN-γ), which not only stimulate local inflammatory responses but also enhance the activity of monocytes and T cells, thereby contributing to a more robust immune response [ 7 ] . Moreover, the levels of low-density neutrophils (LDG), a distinct subpopulation of neutrophils present within peripheral blood mononuclear cells (PBMC), are markedly increased in the peripheral blood of individuals with active tuberculosis when compared to healthy controls (HC). Notably, the level of LDG declined during the treatment process, reinforcing the idea that elevated LDG counts are linked to the exacerbation of tuberculosis severity [ 8 , 9 ] . CD177 is a glycoprotein that is predominantly found on the surface of neutrophils, playing a critical role in the adhesion and transmigration of endothelial cells [ 10 ] . Research has indicated that the expression levels of CD177 are significantly modulated in response to various physiological and pathological states [ 11 – 13 ] . For instance, individuals suffering from acute respiratory distress syndrome (ARDS) demonstrate an increased percentage of CD177 + neutrophils, which is associated with the severity of the condition [ 14 ] . Furthermore, the presence of CD177 + neutrophils within the tumor microenvironment of lung adenocarcinoma patients is markedly elevated compared to adjacent normal tissues, which correlates with the clinical features and prognostic outcomes of these patients [ 15 ] . Additionally, CD177 + neutrophils are characterized by their robust chemotactic response to microbial infections and are pivotal in orchestrating the immune response during infectious diseases [ 16 , 17 ] . Nonetheless, the specific role of CD177 + neutrophils in patients with tuberculosis remains to be fully elucidated. In the present study, we conducted flow cytometric analysis to confirm the expression of CD177 in circulating subsets of the LDG and NDG from TB patients and HC. Furthermore , we analyzed the proportion of phenotypic markers CD66b and programmed death receptor 1 (PD1) related to activation and immunosuppression in CD177 + LDG and CD177 + NDG. In addition, we examined their correlation with cytokines and other inflammatory indicators and the diagnostic value of CD177 + neutrophil subsets by performing a receiver operating characteristic (ROC) curve. 2. Materials and methods 2.1. Patients and Data collection A cohort of 42 tuberculosis (TB) patients (23 males; mean age ± standard error of the mean [SEM], 50.79 ± 17.12 years) was recruited from the rheumatology department at the First Affiliated Hospital of Nanchang University (Nanchang, China) between June 2024 and May 2025, namely the TB group. Participants were selected based on specific inclusion criteria, which included a confirmed diagnosis established through clinical evaluations, radiological assessments, and positive sputum cultures for active tuberculosis (ATB). Exclusion criteria encompassed individuals with concurrent chronic illnesses, including but not limited to chronic infections, malignancies, diabetes mellitus, or HIV, as well as those receiving immunosuppressive treatment. Comprehensive experimental data of TB patients were gathered, including measurements of early secretory antigenic target 6 spot-forming cells (ESAT-6 sfc), culture filtrate protein 10 spot-forming cells (CFP-10 sfc), the ratio of Mycobacterium tuberculosis-specific antigens (TBAg) to phytohemagglutinin (PHA) (denoted as TBAg/PHA Ratio), T cell spot test(T-spot)，erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) levels, and cytokines such as interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, tumor necrosis factor-α (TNF-α), and interferon-gamma (IFN-γ). Additionally, routine hematological parameters were assessed, including white blood cell count (WBC), red blood cell count (RBC), platelet count (PLT), hematocrit (HCT), hemoglobin concentration (HB), lymphocyte count (L) and percentage (L%), monocyte count (M) and percentage (M%), neutrophil count (N) and percentage (N%), along with ratios such as lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), platelet-to-monocyte ratio (PMR), monocyte-to-neutrophil ratio (MNR), and platelet-to-neutrophil ratio (PNR). Concurrently, a control group comprising 26 age- and sex-matched healthy participants (17 males; mean age±SEM, 49.77±17.14 years) who tested negative for interferon-gamma release assays (IGRA) and did not exhibit any other inflammatory conditions was assembled as the healthy control (HC) group. Demographic information and characteristics of the patients are shown in Table 1. The research protocol complied with the principles outlined in the Declaration of Helsinki and was approved by the Medical Ethics Committee of the First Affiliated Hospital of Nanchang University [approval no. (2024)CDYFYYLK(07-046)]. 2.2. Materials The antibodies for flow cytometry were used: phycoerythrin-Texas Red tandem(ECD)-conjugated anti-CD14 (SFCI12T4D11 clone, BD Biosciences, San Diego, CA, USA), phycoerythrin-Cyanin 5 (PC5)-conjugated anti-CD15 (80H5 clone, Beckman Coulter, Miami, FL,USA), phycoerythrin (PE)-conjugated anti-CD177 (MEM-166 clone, Molecular Probes, Eugene, OR, USA), phycoerythrin-Cyanin 7 (PC7)-conjugated anti-CD66b (G10F5, eBioscience, San Diego, CA, USA), fluorescein isothiocyanate (FITC)-conjugated anti-PD1 (MIH clone, e Bioscience, San Diego, CA, USA). 2.3 Evaluation of CD177 on LDG and NDG by flow cytometry Approximately 3 ml of blood was obtained from the antecubital vein and transferred into tubes coated with EDTA. Peripheral blood mononuclear cells (PBMCs) were subsequently isolated through density gradient centrifugation utilizing Ficoll-amidotrizoate (LUMC, Leiden, Netherlands), following established protocols [8] . In summary, the venous blood specimens (3 ml) were combined with an equivalent volume of sterile saline solution. The diluted samples underwent density gradient centrifugation at a speed of 300g for a duration of 20 minutes. After centrifugation, PBMCs were meticulously collected from the interface between the plasma and lymphocyte layers for the purpose of analyzing low-density granulocytes (LDGs). The PBMC fraction was treated with a specialized erythrocyte lysis buffer (OptiLyse C; Beckman Coulter, Brea, CA, USA) to remove the contamination from red blood cells. The NDGs were then isolated from the residual red blood cell pellet through dextran sedimentation, followed by additional lysis steps for erythrocytes. Following this, 50 uL of freshly prepared PBMCs (5 × 10 5 ) or 100 uL of NDG (6 × 10 5 ) were incubated concurrently with 4 μL of ECD-conjugated anti-CD14, 4 μL of PC5-conjugated anti-CD15, 4 μL of PE-conjugated anti-CD177, and 4 μL of FITC-conjugated anti-PD1 in a dark environment for 15 minutes. Subsequently, the cells were evaluated employing a CYTOMICS FC 500 flow cytometer and CXP software (Beckman Coulter Inc., Brea, CA, USA). Additionally, CD66b (CEACAM-8, carcinoembryonic antigen-related cell adhesion molecule 8), serving as an activation marker, and PD-1 (Programmed Death receptor 1), acting as an immune modulation marker for both LDG and NDG, were also assessed. 2.4 CRP, ESR, routine blood measurements and cytokines CRP levels in the serum of patients with TB were determined using nephelometry, according to the manufacturer's instructions (IMMAGE ® 800 protein chemistry analyzer; Beckman Coulter, Inc.). ESR and routine blood tests were performed according to the manufacturer’s instructions (automatic measuring instrument for eSr Xc-40B, Pu li Sheng, China. Sysmex Xe-2100 analyzer, Sysmex, Kobe, Japan). Based on the routine blood measurement results, indicators of inflammation, including LMR, NLR, PLR, SII, and dNLR, were calculated using a previously described formula[LMR=L / M, NLR=N / L, PLR=PLT / L, SII=PLT * N/L, dNLR=N / (WBC-N), PMR (PLT / M), MNR (M / N), and PNR (PLT / N)] [18] . Serum samples collected at diagnosis were used to measure serum cytokine levels. The levels of IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, TNF-α, and IFN-γ were measured with cytokine profiling kits (Siemens Healthcare (Pty) Ltd.) using an Immulite® 1000 Immunoassay System (Siemens Healthcare (Pty) Ltd), according to the manufacturer’s instructions. 2.5 Statistical analysis Data analysis was performed using the FlowJo v10.8.1 software (BD, Ashland, OR, USA) and GraphPad Prism. The expression of each individual surface marker was represented by the MFI or percentage. Data are presented as mean ± standard deviation or median and interquartile range (IQR, 25th to 75th percentile). Comparisons between two unpaired groups were analyzed using an independent sample unpaired t-test or non-parametric Mann-Whitney U test. Correlation analysis was performed using Pearson’s or Spearman's correlation test. The ROC curve and area under the curve (AUC) were analyzed using GraphPad Prism software. P < 0.05 was considered statistically significant. 3. Results 3.1 Baseline characteristics As shown in Table 1 , A total of 68 participants were included in this study, comprising 42 patients with TB and 26 HC. The TB group exhibited significant differences compared to the HC group in all measured variables, except for age, gender, WBC, PLT, as well as M, N, SII, PMR, and MNR. The affected anatomical sites among TB patients was distributed sequentially in lungs, Intestine, lumbar spine, lymph nodes, cervical spine, abdominal cavity, pleura, spine, esophage. Moreover, the symptom of expectorating phlegm was predominantly observed in 9 patients (21.4%) diagnosed with TB, followed by pain (19.0%), fever(9.5%), and chest tightness (7.1%). Twenty-four patients were positive for T-SPOT. Hematological parameters showed that RBC, HB, HCT, L, PLR, and PNR were significantly lower in TB patients compared to HC, whereas NLR and dNLR were also significantly higher in TB patients compared to HC. 3.2 Expression of CD177 + LDG and CD177 + NDG in TB patients LDG and NDG were extracted from peripheral blood and subjected to analyse the expression of CD177 by flow cytometry. The expression of CD177 + LDG and CD177 + NDG in patients with TB (n = 42) and HC (n = 26) was analyzed. We observed that the percentage of CD177 + NDG was lower in the TB group than in the HC group ( P < 0.05) (Fig. 1 C), whereas the MFI of CD177 in the LDG was significantly higher in the TB group than in the HC group (Fig. 1 D). While no significant difference was observed in the MFI of CD177 in the NDG and percentage of CD177 + LDG in TB and HC group (Fig. 1 B, E). These differential expression patterns likely reflect alterations in the immunological profile of tuberculosis infection. 3.3 Expression of CD66b and PD1 on CD177 + LDG and CD177 + NDG in TB and extra-pulmonary tuberculosis ( EPTB) We next compared the expression CD177 in LDG and NDG in TB patients. Data showed the percentage of CD177 were not significantly different between LDG and NDG (Fig. 2 A), and the MFI of CD177 in the LDG was significantly higher than that in the NDG in the TB group ( P < 0.05, Fig. 2 B). Many reports indicated that CD66b and PD1 play an important role in TB. Subsequently, we attempted to ascertain whether the expression level of CD177 is associated with the activation markers of CD66b and immunosuppression marker PD1 of the LDG and NDG in 27 TB patients. The data indicated that the MFI of CD66b of the LDG was significantly higher than that of the NDG in the TB group ( P < 0.05, Fig. 2 D). Meanwhile, CD177 + granulocytes showed high CD66b and low PD1. The percentage of CD66b (Fig. 2 E) and PD1 (Fig. 2 F) on CD177 + LDG was higher than those on CD177 + ND G ( P < 0.05). Furthermore, the MFI of CD66b (Fig. 2 G) and PD1 (Fig. 2 H) on CD177 + LDG was also higher than that of CD177 + NDG ( P < 0.05). In addition, we observed that the expression of CD177 + LDG differed among different types of tuberculosis patients. Specifically, 42 patients with TB were divided into 23 pulmonary tuberculosis (PTB) and 19 extrapulmonary tuberculosis (EPTB). As shown in Fig. 3 , the percentage of CD177 + LDG (Fig. 3 A), the percentage of PD1 of CD177 + LDG (Fig. 3 B) and MFI of PD1 of CD177 + LDG (Fig. 3 C) were all significantly increased in the EPTB group compared to the PTB group ( P 0.05). 3.4 Correlation between the expression of CD177 and CD66b, PD1 on LDG and NDG and clinical variables. WBC, L, M, N, LMR, NLR, PLR, SII, dNLR, PMR, MNR, PNR, ESR, CRP, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, TNF-α, and IFN-γ, the common predictors of inflammation, were investigated and analyzed for their correlations with the expression of CD177 in the present study in patients with TB. We also investigated the relationship between the expression of CD177 and CD66b, PD1. Our study revealed that a weak but significant correlation was observed between the MFI of CD177 in LDG and MFI of CD66b of LDG (r = 0.5531, P < 0.05, Fig. 4 A), and between the percentage of CD177 + NDG and MFI of PD1 of NDG (r = -0.4001, P < 0.05, Fig. 4 B). Additionally, the MFI of CD177 of NDG correlated with the MFI of CD66b of NDG (r = 0.5525 , P < 0.05, Fig. 4 C). No significant difference s were observed among the others (data not shown). 3.5 ROC analysis ROC curves were generated to evaluate the diagnostic performance of CD177 expression and related markers in distinguishing patients with TB from healthy controls, LDG from NDG, and EPTB from PTB. The analysis revealed that the percentage of CD177 + NDG showed the highest potential in distinguishing between patients with TB and HC, achieving 90.00% sensitivity and 59.26% specificity with an AUC of 0.748, followed by the MFI of CD177 of LDG with 57.69% sensitivity and 81.00% specificity (AUC = 0.715) (Fig. 5 A). Notably, MFI of PD1 on CD177 + LDG harbored the highest AUC to differentiate EPTB and PTB (AUC = 0.818 ) with 70.00% sensitivity and 88.24% specificity (Fig. 5 B). 4. Discussion CD177 (also known as NB1 antigen or HNA-2a antigen) is a glycoprotein with a molecular weight of approximately 50–60 kDa that is specifically expressed on the plasma and secretory granule membranes of neutrophils [ 19 ] . The percentage of CD177-positive neutrophils in circulation remains consistent within individuals and is unaffected by age, sex, or cellular activation status. However, this proportion rises in specific contexts, including pregnancy, administration of granulocyte-colony stimulating factor (G-CSF), individuals with systemic lupus erythematosus (SLE), ANCA-associated systemic vasculitis (AASV), heatstroke, acute-on-chronic liver failure, periodontitis, severe systemic infections and polycythemia vera (PV) [ 20 – 28 ] . Thus, we hypothesize d that CD177 + granulocytes may increase the incidence of inflammatory disease s, especially TB. As expected, we found that the MFI of CD177 in the LDG was significantly higher in the TB group than in the HC group . This finding aligns with previous studies that have identified CD177 + neutrophils as a distinct subpopulation with enhanced inflammatory responses. For instance, CD177 + neutrophils have been shown to exhibit increased migration to inflamed tissues and enhanced production of reactive oxygen species, which are critical in combating infections [ 27 , 29 ] . Recent research underscores the functional diversity of neutrophils, particularly highlighting the distinctive transcriptomic characteristics of CD177 + neutrophils that bolster their pro-inflammatory functions [ 30 , 31 ] . This functional differentiation could be especially pertinent in the context of tuberculosis (TB), where the immune response must navigate the delicate balance between eradicating pathogens and preserving tissue integrity to avert excessive damage. In addition to the imbalance in neutrophil subsets, dysregulated activation of neutrophils is another characteristic of TB. CD66b is expressed on specific granules and is usually used to evaluate neutrophil activation in TB [ 32 ] . In this study, we demonstrated that CD177 + granulocytes expressed high levels of CD66b and low levels of PD1. Additionally, the MFI of CD177 in the LDG was significantly higher than that in the NDG of the TB patients, and the percentage and MFI of CD66b and PD1 on CD177 + LDG was higher than those on CD177 + ND G . Moreover, CD177 + LDG and CD177 + NDG was associated with CD66b, PD1, and CFP-10 sfc in TB patients and showed good performance in distinguishing between TB and HC, PTB and EPTB. Our findings, for the first time, revealed the pathogenic neutrophil subsets, namely CD177 + LDG and CD177 + NDG, may serve as diagnostic biomarker s of TB. CD177⁺ LDG expressed significantly more CD66b (specific granules) than CD177⁺ NDG, which suggested a possible dominant degranulation property of CD177⁺ LDG. There were notable associations observed between the CD177 MFI on LDG and CD66b MFI, along with CFP-10 sfc, which reinforced the notion that CD177⁺ LDG may possess pro-inflammatory characteristics in an activated state. Consistent with its pro-inflammatory characteristics, the expression of CD177, a specific neutrophil activation marker, has been reported to contribute to predict the severity and mortality at COVID-19 the gene and protein level s [ 33 ] . This also supports the observation that TB involves an imbalance in granulocyte subsets and that the abnormal expression of key signaling molecules on neutrophils plays an important role in TB pathogenesis [ 8 , 9 ] . Interest ingly, a previous study revealed that CD177 pos neutrophils exhibited reduced secretion of pro-inflammatory cytokines but elevated production of IL-22 and transforming growth factor-β (TGF-β) [ 24 ] in inflammatory bowel disease (IBD). Moreover, CD177 + neutrophils exhibit enhanced ability to produce NETs and contribute to organ damage during heatstroke [ 26 ] . In addition, the proportion of CD177-positive neutrophils is increased in the hepatic tissues of patients with biliary atresia, and the expression levels of IFN and degranulation-related genes were elevated in CD177-positive neutrophils [ 34 ] . These findings strengthen the advantage of utilizing CD177 as a pro-inflammatory biomarker in patients with TB . Finally, we conducted roc to anaylze the performance of the CD177 + granulocytes and found the percentage of CD177 + NDG showed 90.00% sensitivity and 59.26% specificity with an AUC of 0.748 in distinguishing between patients with TB and HC , followed by the MFI of CD177 of LDG. Notably, MFI of PD1 on CD177 + LDG harbored the highest AUC to differentiate EPTB and PTB (AUC = 0.818 ) with 70.00% sensitivity and 88.24% specificity, which strengthed that CD177 + LDG and CD177 + NDG could serve as diagnostic biomarker s of TB. Our study had several limitations. First, this was a single-center study and the observed association between CD177 + granulocytes and TB requires large sample size study for validation in a multic enter cohort . Second, additional mechanistic investigations are needed to better understand the role of CD177 in granulocyte migration, cytokine release, and T-cell suppression in TB in the cellular or animal level. Future research can describe the expression characteristics and biological significance of CD177 in granulocyte subsets more accurately through large-scale clinical sample analysis and single-cell RNA sequencing technology. 5. Conclusion Our study revealed t he MFI of CD177 on LDG was significantly increased, and the percentage of CD177 + NDG was decreased in the TB group compared to that in the HC group, as determined by flow cytometry. CD177⁺ LDG are characterized by high CD66b and low PD1, and showed a certain correlation with CD66b and CFP − 10 sfc. Their strong diagnostic performance in TB and HC, PTB and EPTB supported their potential as reliable diagnostic biomarkers. Our research established ROC to distinguish TB and HC, PTB and EPTB , which might improve our understanding of the role of CD177 + granulocytes in TB. Abbreviations NDG normal density granulocytes LDG low density granulocytes ROC receiver operating characteristic PLT platelet count NLR neutrophil-to-lymphocyte ratio TNF-α tumor necrosis factor-α CFP-10 SFC culture filtrate protein 10 spot-forming cells IFN-γ interferon-γ Mtb Mycobacterium tuberculosis TB Tuberculosis NETs neutrophil extracellular traps PTB pulmonary tuberculosis patients IL: interleukin IL-1β Interleukin-1 beta PBMC peripheral blood mononuclear cells HC healthy controls ARDS acute respiratory distress syndrome ATB active tuberculosis patients LTBI latent tuberculosis infections ESAT-6 sfc Early secretory antigenic target 6 spot-forming cells TBAg Mtb-specific antigens PHA phytohemagglutinin ESR erythrocyte sedimentation rate CRP C-reactive protein WBC white blood cell count RBC red blood cell count PLT platelet count HCT hematocrit HB hemoglobin L lymphocyte count L% lymphocyte percentage M monocyte count M% monocyte percentage N neutrophil count N% neutrophil percentage LMR lymphocyte-to-monocyte ratio NLR neutrophil-to-lymphocyte ratio dNLR derived NLR PLR platelet-to-lymphocyte ratio SII systemic immune inflammation index PMR platelet to monocyte ratio MNR monocyte to neutrophil ratio PNR platelet to neutrophil ratio IGRA interferon-gamma release assays PC phycoerythrin-Cyanin ECD phycoerythrin-Texas Red tandem FITC fluorescein isothiocyanate PE phycoerythrin PD-1 Programmed Death receptor 1 MFI mean fluorescence intensity IQR interquartile range AUC the area under the curve EPTB extrapulmonary tuberculosis G-CSF granulocyte-colony stimulating factor SLE individuals with systemic lupus erythematosus AASV ANCA-associated systemic vasculitis PV polycythemia vera TGF-β transforming growth factor-β IBD inflammatory bowel disease. Declarations Ethics approval and informed consent The study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the Medical Ethical Committees of the First Affiliated Hospital of Nanchang University [approval no. (2024)CDYFYYLK(07-046)]. Informed consent was obtained from all subjects involved in the study. Consent for publication All the listed authors have carefully reviewed and approved this manuscript. Availability of data and materials The original contributions of this study are included in the article and supplementary material. Further inquiries can be directed toward the corresponding author. Conflicts of interest The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest. Founding This research was funded by Education Department of Jiangxi Province (GJJ2200216); Natural Science Foundation of Jiangxi province(20212BAB216028). Author Contributions Funding acquisition: Xue Li, Zai chuan Lin and Rigu Su; Funding acquisition: Xue Li; Investigation, Zai chuan Lin; Project administration: Xue Li, Zikun Huang, and Junming Li; Resources: Jun Liu; Software: Qing Luo; Supervision: Qing Luo; Validation: Xue Li and Zai chuan Lin; Visualization: Rigu Su; Writing – original draft: Xue Li and Zai chuan Lin; Writing – review and editing: Zikun Huang and Junming Li. References Garg T, Rath G, Murthy RR, Gupta UD, Vatsala PG, Goyal AK. Current Nanotechnological Approaches for an Effective Delivery of Bioactive Drug Molecules to Overcome Drug Resistance Tuberculosis. Curr Pharm Des. 2015 ; 21(22):3076-89. doi:10.2174/1381612821666150531163254 World Health Organization (2024). Global Tuberculosis Report 2024 Factsheet. 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Demographic information and characteristics of TB patients and healthy controls. characteristics TB HC P value n 42 26 Gender, male, n (%) 23 (33.8%) 17 (25%) 0.237 Age, mean ± sd 50.79 ± 17.12 49.77 ± 17.14 0.813 Distribution sites Lungs, n (%) 23 (54.80%) Intestine, n (%) 4 (9.50%) Lumbar spine, n (%) 4 (9.50%) Lymph nodes, n (%) 3 (7.10%) Cervical spine, n (%) 2 (4.80%) Abdominal cavity, n (%) 2 (4.80%) Pleura, n (%) 2 (4.80%) Spine, n (%) 1 (2.40%) Esophage, n (%) 1 (2.40%) Clinical features Coughing phlegm, n (%) 9 (21.40%) Pain, n (%) 8 (190%) Fever, n (%) 4 (9.50%) Chest tightness, n (%) 3 (7.10%) Rash, n (%) 1 (2.40%) Numbness, n (%) 1 (2.40%) Diarrhea, n (%) 1 (2.40%) Fatigue, n (%) 1 (2.80%) Experimental data ESR, mean ± sd 38.29 ± 32.32 CRP, mean ± sd 18.17 ± 31.89 T-spot, positive, n (%) 24 (75%) 0 (0%) WBC, median (IQR) 5.4 (4.63, 6.94) 6.09 (5.07, 7.15) 0.354 RBC, mean ± sd 4.44 ± 0.62 4.82 ± 0.42 0.009 HB, mean ± sd 128.67 ± 21.52 147.75 ± 14.90 < 0.001*** HCT, mean ± sd 0.39 ± 0.06 43.59 ± 3.88 < 0.001*** PLT, median (IQR) 201.5 (172, 262) 232 (203.75, 270.75) 0.105 L, median (IQR) 1.185 (0.96, 1.77) 2.105 (1.74, 2.44) < 0.001*** M, median (IQR) 0.40351 (0.29, 0.56) 0.425 (0.37, 0.50) 0.505 N, median (IQR) 3.28 (2.99, 4.43) 3.285 (2.52, 3.99) 0.283 LMR, median (IQR) 2.3901 (1.61, 4.47) 1.543 (1.29, 1.84) 0.003 NLR, median (IQR) 285.47 (172.86, 404.16) 464.14 (362.62, 737.56) 0.002 dNLR, median (IQR) 1.856 (1.35, 2.66) 1.1972 (1.03, 1.39) < 0.001*** PLR, median (IQR) 0.5058 (0.32, 0.93) 0.8998 (0.69, 1.26) 0.019 SII, median (IQR) 497.93 (284.66, 1033.50) 345.88 (299.73, 459.20) 0.084 PMR, median (IQR) 530.51 (371.70, 805.78) 540.95 (485.37, 649.36) 0.724 MNR, median (IQR) 0.11 (0.08, 0.14) 0.1325 (0.11, 0.15) 0.05 PNR, median (IQR) 59.472 (51.57, 77.48) 76.475 (59.91, 90.79) 0.018 Abbreviations:TB: tuberculosis, HC: healthy controls, ESR: erythrocyte sedimentation rate, CRP: C-reactive protein, T-spot: T Cell Spot Test, WBC:white blood cell count, IQR: interquartile range, RBC: red blood cell count, PLT: platelet count, HCT: hematocrit, HB: hemoglobin, L: lymphocyte count, M: monocyte count, N: neutrophil count, LMR: lymphocyte-to-monocyte ratio, NLR: neutrophil-to-lymphocyte ratio, dNLR: derived NLR, PLR: platelet-to-lymphocyte ratio, SII: systemic immune inflammation index, PMR: platelet to monocyte ratio, MNR: monocyte to neutrophil ratio, PNR: platelet to neutrophil ratio. *P value for TB group and HC group, ***: p < 0.001. 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1","display":"","copyAsset":false,"role":"figure","size":131010,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the expression of CD177 on LDG and NDG in TB patients and HC by flow cytometry. LDG and NDG were isolated using Ficoll gradient. NDG were was as follows: granulocytes were first selected by size (FSC) and granularity (SSC) analyses, and LDG were identified as CD14\u003csup\u003elow\u003c/sup\u003e\u0026nbsp;CD15\u003csup\u003e+\u003c/sup\u003e\u0026nbsp;cells within PBMC. NDG was defined as CD15\u003csup\u003ehigh\u003c/sup\u003e CD14\u003csup\u003e-\u003c/sup\u003e in the purified erythrocyte fraction. CD177\u003csup\u003e+ \u003c/sup\u003eLDG and NDG were defined as LDG and NDG with CD177-PE fluorescence intensity above the threshold set by the isotype control. (B)(C) Dot plots of the percentage of CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG in healthy controls (n = 26) and TB patients (n = 42). (D)(E) The MFI of CD177 of LDG and NDG in healthy controls (n = 26) and TB patients (n = 42). HC: healthy controls. NDG: normal density granulocytes. LDG: low density granulocytes. MFI: mean fluorescence intensity.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7809533/v1/0859117d78aabe68ffa45a77.png"},{"id":95534588,"identity":"ef6ab543-cd0d-47b5-8f37-4f90f0f16bd5","added_by":"auto","created_at":"2025-11-10 10:29:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":139480,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of CD66b and PD1 on CD177 \u003csup\u003e+ \u003c/sup\u003eLDG and CD177\u003csup\u003e + \u003c/sup\u003eNDG in TB and extrapulmonary tuberculosis (EPTB). The expression of CD177 of LDG and NDG in TB patients (n=42)(A, B). The expression of activation marker CD66b of LDG and NDG in TB patients (n=42)(C, D). The expression of activation marker CD66b and immunosuppression marker PD1 of the CD177\u003csup\u003e+\u003c/sup\u003eLDG and CD177\u003csup\u003e+\u003c/sup\u003eNDG in TB patients (n=27) (A, C). The percentage and MFI of CD66b between CD177\u003csup\u003e+ \u003c/sup\u003eLDG and CD177\u003csup\u003e+ \u003c/sup\u003eNDG (E, G). The percentage and MFI of PD1 between CD177\u003csup\u003e+ \u003c/sup\u003eLDG and CD177\u003csup\u003e+ \u003c/sup\u003eNDG (F, H).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7809533/v1/71993e4b6b8a56d225b8a0ee.png"},{"id":95534553,"identity":"04b0fd73-f769-4c12-a125-dc140b634801","added_by":"auto","created_at":"2025-11-10 10:29:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48820,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression of CD177 of LDG and NDG in PTB group and EPTB group. (A) The percentage of CD177 of LDG in PTB group (n=23) and EPTB group (n=19). (B) The percentage of PD1 of CD177\u003csup\u003e+ \u003c/sup\u003eLDG between PTB group (n=17) and EPTB group (n=10). (C) The MFI of PD1 of CD177\u003csup\u003e+ \u003c/sup\u003eLDG between PTB group (n=17) and EPTB group (n=10). PTB: pulmonary tuberculosis, EPTB: extrapulmonary tuberculosis, PD-1: programmed cell death 1.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7809533/v1/484748faff3e998ffb08f130.png"},{"id":95534767,"identity":"89418eb9-bb72-445e-97ec-5ca70c9e7b96","added_by":"auto","created_at":"2025-11-10 10:29:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":36299,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between the expression of CD177 and CD66b, PD1, and clinical characteristics.The correlation between the MFI of CD177 on LDG and CD66b (A) and culture filtrate protein 10 spot-forming cells (CFP-10 sfc) (C). (B) The correlation between the percentage of CD177\u003csup\u003e+ \u003c/sup\u003eNDG and MFI of PD1 NDG.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7809533/v1/8cd4fedc785c36f7018c3306.png"},{"id":95534540,"identity":"ea6771f8-9115-45af-bc1e-b7e0819d530d","added_by":"auto","created_at":"2025-11-10 10:29:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":45882,"visible":true,"origin":"","legend":"\u003cp\u003eROC analysis. (A) ROC curve analysis of the performance of the MFI of CD177 on LDG and the percentage of CD177\u003csup\u003e+ \u003c/sup\u003eNDG in TB patients and HC. (B) ROC curve analysis of the percentage of CD177\u003csup\u003e+ \u003c/sup\u003eLDG, the percentage and MFI of PD1 of CD177\u003csup\u003e+ \u003c/sup\u003eLDG in EPTB and PTB patients.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7809533/v1/0b1e770ce54f777b8beae957.png"},{"id":99315111,"identity":"a269b618-3229-4cb3-a9a5-7a8f0f303cfd","added_by":"auto","created_at":"2025-12-31 16:26:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1311743,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7809533/v1/592f6113-4455-483a-8a69-a70b8ba1842d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the expression and diagnostic value of CD177 + neutrophils in tuberculosis patients","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMycobacterium tuberculosis (Mtb) is an obligate aerobic and non-motile pathogenic bacterium primarily transmitted through respiratory droplets. The disease tuberculosis (TB), which is instigated by Mtb, continues to pose a significant challenge to global health. According to the World Health Organization's 2023 epidemiological report\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e, there were approximately 10.8\u0026nbsp;million newly reported cases of TB and 1.25\u0026nbsp;million deaths linked to this disease. It is noteworthy that TB has recently overtaken COVID-19, becoming the foremost cause of mortality among infectious agents globally, despite the ongoing advancements in treatment options \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. The pathophysiological mechanisms underlying tuberculosis are intricate, involving the host's immune response, the biological properties of the bacterium, and various environmental influences \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNeutrophils are crucial in the processes of engulfing and eradicating pathogens during the initial phases of infection, employing mechanisms such as phagocytosis, oxidative burst, and the generation of neutrophil extracellular traps (NETs) \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. In patients suffering from pulmonary tuberculosis (PTB), the extent of tissue damage in the lungs is significantly associated with both the quantity and the functional status of neutrophils \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Normal-density granulocytes (NDG) are involved in the direct destruction of Mycobacterium tuberculosis (MTB) and play a regulatory role in the immune response by releasing cytokines and chemokines. These neutrophils can produce various cytokines, including interleukin 6 (IL-6), interleukin-1 beta (IL-1β), and interferon-γ (IFN-γ), which not only stimulate local inflammatory responses but also enhance the activity of monocytes and T cells, thereby contributing to a more robust immune response \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Moreover, the levels of low-density neutrophils (LDG), a distinct subpopulation of neutrophils present within peripheral blood mononuclear cells (PBMC), are markedly increased in the peripheral blood of individuals with active tuberculosis when compared to healthy controls (HC). Notably, the level of LDG declined during the treatment process, reinforcing the idea that elevated LDG counts are linked to the exacerbation of tuberculosis severity \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCD177 is a glycoprotein that is predominantly found on the surface of neutrophils, playing a critical role in the adhesion and transmigration of endothelial cells \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Research has indicated that the expression levels of CD177 are significantly modulated in response to various physiological and pathological states \u003csup\u003e[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. For instance, individuals suffering from acute respiratory distress syndrome (ARDS) demonstrate an increased percentage of CD177\u003csup\u003e+\u003c/sup\u003e neutrophils, which is associated with the severity of the condition \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Furthermore, the presence of CD177\u003csup\u003e+\u003c/sup\u003e neutrophils within the tumor microenvironment of lung adenocarcinoma patients is markedly elevated compared to adjacent normal tissues, which correlates with the clinical features and prognostic outcomes of these patients \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Additionally, CD177\u003csup\u003e+\u003c/sup\u003e neutrophils are characterized by their robust chemotactic response to microbial infections and are pivotal in orchestrating the immune response during infectious diseases \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Nonetheless, the specific role of CD177\u003csup\u003e+\u003c/sup\u003e neutrophils in patients with tuberculosis remains to be fully elucidated.\u003c/p\u003e\u003cp\u003eIn the present study, we conducted flow cytometric analysis to confirm the expression of CD177 in circulating subsets of \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe LDG\u003c/span\u003e and NDG from \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eTB\u003c/span\u003e patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand HC. Furthermore\u003c/span\u003e, we analyzed the proportion of phenotypic markers CD66b and programmed death receptor 1 (PD1) related to activation and immunosuppression in CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG. In addition, we examined their correlation with cytokines and other inflammatory indicators and the diagnostic value of CD177\u003csup\u003e+\u003c/sup\u003e neutrophil subsets by performing a receiver operating characteristic (ROC) curve.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e2.1. Patients and Data collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cohort of 42 tuberculosis (TB) patients (23 males; mean age ± standard error of the mean [SEM], 50.79 ± 17.12 years) was recruited from the rheumatology department at the First Affiliated Hospital of Nanchang University (Nanchang, China) between June 2024 and May 2025, namely the TB group. Participants were selected based on specific inclusion criteria, which included a confirmed diagnosis established through clinical evaluations, radiological assessments, and positive sputum cultures for active tuberculosis (ATB). Exclusion criteria encompassed individuals with concurrent chronic illnesses, including but not limited to chronic infections, malignancies, diabetes mellitus, or HIV, as well as those receiving immunosuppressive treatment.\u003c/p\u003e\n\u003cp\u003eComprehensive experimental data of TB patients were gathered, including measurements of early secretory antigenic target 6 spot-forming cells (ESAT-6 sfc), culture filtrate protein 10 spot-forming cells (CFP-10 sfc), the ratio of Mycobacterium tuberculosis-specific antigens (TBAg) to phytohemagglutinin (PHA) (denoted as TBAg/PHA Ratio), T cell spot test(T-spot)，erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) levels, and cytokines such as interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, tumor necrosis factor-α (TNF-α), and interferon-gamma (IFN-γ). Additionally, routine hematological parameters were assessed, including white blood cell count (WBC), red blood cell count (RBC), platelet count (PLT), hematocrit (HCT), hemoglobin concentration (HB), lymphocyte count (L) and percentage (L%), monocyte count (M) and percentage (M%), neutrophil count (N) and percentage (N%), along with ratios such as lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), platelet-to-monocyte ratio (PMR), monocyte-to-neutrophil ratio (MNR), and platelet-to-neutrophil ratio (PNR). \u003c/p\u003e\n\u003cp\u003eConcurrently, a control group comprising 26 age- and sex-matched healthy participants (17 males; mean age±SEM, 49.77±17.14 years) who tested negative for interferon-gamma release assays (IGRA) and did not exhibit any other inflammatory conditions was assembled as the healthy control (HC) group. Demographic information and characteristics of the patients are shown in Table 1. The research protocol complied with the principles outlined in the Declaration of Helsinki and was approved by the Medical Ethics Committee of the First Affiliated Hospital of Nanchang University [approval no. (2024)CDYFYYLK(07-046)].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe antibodies for flow cytometry were used: phycoerythrin-Texas Red tandem(ECD)-conjugated anti-CD14 (SFCI12T4D11 clone, BD Biosciences, San Diego, CA, USA), phycoerythrin-Cyanin 5 (PC5)-conjugated anti-CD15 (80H5 clone, Beckman Coulter, Miami, FL,USA), phycoerythrin (PE)-conjugated anti-CD177 (MEM-166 clone, Molecular Probes, Eugene, OR, USA), phycoerythrin-Cyanin 7 (PC7)-conjugated anti-CD66b (G10F5, eBioscience, San Diego, CA, USA), fluorescein isothiocyanate (FITC)-conjugated anti-PD1 (MIH clone, e Bioscience, San Diego, CA, USA). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Evaluation of CD177 on LDG and NDG by flow cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproximately 3 ml of blood was obtained from the antecubital vein and transferred into tubes coated with EDTA. Peripheral blood mononuclear cells (PBMCs) were subsequently isolated through density gradient centrifugation utilizing Ficoll-amidotrizoate (LUMC, Leiden, Netherlands), following established protocols\u003csup\u003e[8]\u003c/sup\u003e. In summary, the venous blood specimens (3 ml) were combined with an equivalent volume of sterile saline solution. The diluted samples underwent density gradient centrifugation at a speed of 300g for a duration of 20 minutes. After centrifugation, PBMCs were meticulously collected from the interface between the plasma and lymphocyte layers for the purpose of analyzing low-density granulocytes (LDGs). The PBMC fraction was treated with a specialized erythrocyte lysis buffer (OptiLyse C; Beckman Coulter, Brea, CA, USA) to remove the contamination from red blood cells. The NDGs were then isolated from the residual red blood cell pellet through dextran sedimentation, followed by additional lysis steps for erythrocytes. Following this, 50 uL of freshly prepared PBMCs (5 × 10\u003csup\u003e5\u003c/sup\u003e) or 100 uL of NDG (6 × 10\u003csup\u003e5\u003c/sup\u003e) were incubated concurrently with 4 μL of ECD-conjugated anti-CD14, 4 μL of PC5-conjugated anti-CD15, 4 μL of PE-conjugated anti-CD177, and 4 μL of FITC-conjugated anti-PD1 in a dark environment for 15 minutes. Subsequently, the cells were evaluated employing a CYTOMICS FC 500 flow cytometer and CXP software (Beckman Coulter Inc., Brea, CA, USA). Additionally, CD66b (CEACAM-8, carcinoembryonic antigen-related cell adhesion molecule 8), serving as an activation marker, and PD-1 (Programmed Death receptor 1), acting as an immune modulation marker for both LDG and NDG, were also assessed. \u003c/p\u003e\n\u003ch3\u003e2.4 CRP, ESR, routine blood measurements and cytokines \u003c/h3\u003e\n\u003cp\u003eCRP levels in the serum of patients with TB were determined using nephelometry, according to the manufacturer's instructions (IMMAGE\u003csup\u003e®\u003c/sup\u003e 800 protein chemistry analyzer; Beckman Coulter, Inc.). ESR and routine blood tests were performed according to the manufacturer’s instructions (automatic measuring instrument for eSr Xc-40B, Pu li Sheng, China. Sysmex Xe-2100 analyzer, Sysmex, Kobe, Japan). Based on the routine blood measurement results, indicators of inflammation, including LMR, NLR, PLR, SII, and dNLR, were calculated using a previously described formula[LMR=L / M, NLR=N / L, PLR=PLT / L, SII=PLT * N/L, dNLR=N / (WBC-N), PMR (PLT / M), MNR (M / N), and PNR (PLT / N)]\u003csup\u003e[18]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eSerum samples collected at diagnosis were used to measure serum cytokine levels. The levels of IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, TNF-α, and IFN-γ were measured with cytokine profiling kits (Siemens Healthcare (Pty) Ltd.) using an Immulite® 1000 Immunoassay System (Siemens Healthcare (Pty) Ltd), according to the manufacturer’s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis was performed using the FlowJo v10.8.1 software (BD, Ashland, OR, USA) and GraphPad Prism. The expression of each individual surface marker was represented by the MFI or percentage. Data are presented as mean ± standard deviation or median and interquartile range (IQR, 25th to 75th percentile). Comparisons between two unpaired groups were analyzed using an independent sample unpaired t-test or non-parametric Mann-Whitney U test. Correlation analysis was performed using Pearson’s or Spearman's correlation test. The ROC curve and area under the curve (AUC) were analyzed using GraphPad Prism software. \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Baseline characteristics\u003c/h2\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, A total of 68 participants were included in this study, comprising 42 patients with TB and 26 HC. The TB group exhibited significant differences compared to the HC group in all measured variables, except for age, gender, WBC, PLT, as well as M, N, SII, PMR, and MNR. The affected anatomical sites among TB patients was distributed sequentially in lungs, Intestine, lumbar spine, lymph nodes, cervical spine, abdominal cavity, pleura, spine, esophage. Moreover, the symptom of expectorating phlegm was predominantly observed in 9 patients (21.4%) diagnosed with TB, followed by pain (19.0%), fever(9.5%), and chest tightness (7.1%). Twenty-four patients were positive for T-SPOT. Hematological parameters showed that RBC, HB, HCT, L, PLR, and PNR were significantly lower in TB patients compared to HC, whereas NLR and dNLR were also significantly higher in TB patients compared to HC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Expression of CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG in TB patients\u003c/h2\u003e\u003cp\u003eLDG and NDG were extracted from peripheral blood and subjected to analyse the expression of CD177 by flow cytometry. The expression of CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ein\u003c/span\u003e patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewith TB\u003c/span\u003e (n\u0026thinsp;=\u0026thinsp;42) and HC (n\u0026thinsp;=\u0026thinsp;26) was analyzed. We observed that the percentage of CD177\u003csup\u003e+\u003c/sup\u003e NDG was lower in the TB group than in the HC group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), whereas the MFI of CD177 in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe\u003c/span\u003e LDG was significantly higher in the TB group than in the HC group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). While no significant difference was observed in the MFI of CD177 in the NDG and percentage of CD177\u003csup\u003e+\u003c/sup\u003e LDG in TB and HC group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, E). These differential expression patterns likely reflect alterations in the immunological profile of tuberculosis infection.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.3 Expression of CD66b and PD1 on CD177\u003c/b\u003e \u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eLDG and CD177\u003c/b\u003e \u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eNDG in TB and extra-pulmonary tuberculosis (\u003c/b\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eEPTB)\u003c/span\u003e\u003c/p\u003e\u003cp\u003eWe next compared the expression CD177 in LDG and NDG in TB patients. Data showed the percentage of CD177 were not significantly different between LDG and NDG (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), and the MFI of CD177 in the LDG was significantly higher than that in the NDG in the TB group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eMany reports indicated that CD66b and PD1 play an important role in TB. Subsequently, we attempted to ascertain whether the expression level of CD177 is associated with the activation markers of CD66b and immunosuppression marker PD1 of the LDG and NDG in 27 TB patients. The data indicated that \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe\u003c/span\u003e MFI of CD66b of the LDG was significantly higher than that of the NDG in the TB group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Meanwhile, CD177\u003csup\u003e+\u003c/sup\u003e granulocytes showed high CD66b and low PD1. The percentage of CD66b (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE) and PD1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF) on CD177\u003csup\u003e+\u003c/sup\u003e LDG was higher than those on CD177\u003csup\u003e+\u003c/sup\u003e ND\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eG\u003c/span\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eFurthermore, the\u003c/span\u003e MFI of CD66b (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG) and PD1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH) on CD177\u003csup\u003e+\u003c/sup\u003e LDG was also higher than that of CD177\u003csup\u003e+\u003c/sup\u003e NDG (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eIn addition, we observed that the expression of CD177\u003csup\u003e+\u003c/sup\u003e LDG differed among different types of tuberculosis patients. Specifically, 42 patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewith TB were divided into 23 pulmonary tuberculosis (PTB) and 19 extrapulmonary tuberculosis (EPTB). As shown in\u003c/span\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the percentage of CD177\u003csup\u003e+\u003c/sup\u003e LDG (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), the percentage of PD1 of CD177\u003csup\u003e+\u003c/sup\u003e LDG (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and MFI of PD1 of CD177\u003csup\u003e+\u003c/sup\u003e LDG (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC) were all significantly increased in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe EPTB group\u003c/span\u003e compared to \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe PTB group\u003c/span\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewhile others were not (\u003c/span\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.4 Correlation between the expression of CD177 and CD66b, PD1 on LDG and NDG and clinical variables.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWBC, L, M, N, LMR, NLR, PLR, SII, dNLR, PMR, MNR, PNR, ESR, CRP, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, TNF-α, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand\u003c/span\u003e IFN-γ, the common predictors of inflammation, were investigated and analyzed for their correlations with the expression of CD177 in the present study in patients with TB. We also investigated the relationship between the expression of CD177 and CD66b, PD1. Our study revealed that a weak but significant correlation was observed between the MFI of CD177 in LDG and MFI of CD66b of LDG (r\u0026thinsp;=\u0026thinsp;0.5531, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), and between the percentage of CD177\u003csup\u003e+\u003c/sup\u003e NDG and MFI of PD1 of NDG (r = -0.4001, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Additionally, the MFI of CD177 of \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eNDG\u003c/span\u003e correlated with the MFI of CD66b of \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eNDG (r\u0026thinsp;=\u0026thinsp;0.5525\u003c/span\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). No significant difference\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003es\u003c/span\u003e were observed among the others (data not shown).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.5 ROC analysis\u003c/h2\u003e\u003cp\u003eROC curves \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewere generated to evaluate the diagnostic performance of CD177 expression and related markers in distinguishing\u003c/span\u003e patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewith TB from healthy controls, LDG from NDG, and EPTB from PTB.\u003c/span\u003e The analysis revealed that the percentage of CD177\u003csup\u003e+\u003c/sup\u003e NDG showed the highest potential in distinguishing between patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewith TB and HC, achieving 90.00% sensitivity and 59.26% specificity\u003c/span\u003e with an AUC of 0.748, followed by \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe MFI of CD177 of LDG with 57.69% sensitivity and 81.00% specificity\u003c/span\u003e (AUC\u0026thinsp;=\u0026thinsp;0.715) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Notably, MFI of PD1 on CD177\u003csup\u003e+\u003c/sup\u003e LDG harbored the highest AUC to differentiate EPTB and PTB (AUC\u0026thinsp;=\u0026thinsp;0.818 ) with 70.00% sensitivity and 88.24% specificity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eCD177 (also known as NB1 antigen or HNA-2a antigen) is a glycoprotein with a molecular weight of approximately 50\u0026ndash;60 kDa that is specifically expressed on the plasma and secretory granule membranes of neutrophils \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. The percentage of CD177-positive neutrophils in circulation remains consistent within individuals and is unaffected by age, sex, or cellular activation status. However, this proportion rises in specific contexts, including pregnancy, administration of granulocyte-colony stimulating factor (G-CSF), individuals with systemic lupus erythematosus (SLE), ANCA-associated systemic vasculitis (AASV), heatstroke, acute-on-chronic liver failure, periodontitis, severe systemic infections and polycythemia vera (PV)\u003csup\u003e[\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24 CR25 CR26 CR27\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Thus, we hypothesize\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ed that CD177\u003c/span\u003e\u003csup\u003e+\u003c/sup\u003e granulocytes may increase the incidence of inflammatory disease\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003es, especially\u003c/span\u003e TB. As expected, we found that \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe\u003c/span\u003e MFI of CD177 in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe\u003c/span\u003e LDG was significantly higher in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe TB group\u003c/span\u003e than in the HC \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003egroup\u003c/span\u003e. This finding aligns with previous studies that have identified CD177\u003csup\u003e+\u003c/sup\u003e neutrophils as a distinct subpopulation with enhanced inflammatory responses. For instance, CD177\u003csup\u003e+\u003c/sup\u003e neutrophils have been shown to exhibit increased migration to inflamed tissues and enhanced production of reactive oxygen species, which are critical in combating infections \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Recent research underscores the functional diversity of neutrophils, particularly highlighting the distinctive transcriptomic characteristics of CD177\u003csup\u003e+\u003c/sup\u003e neutrophils that bolster their pro-inflammatory functions \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. This functional differentiation could be especially pertinent in the context of tuberculosis (TB), where the immune response must navigate the delicate balance between eradicating pathogens and preserving tissue integrity to avert excessive damage.\u003c/p\u003e\u003cp\u003eIn addition to the imbalance in neutrophil subsets, dysregulated activation of neutrophils is another characteristic of TB. CD66b is expressed on specific granules and \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eis usually used to evaluate\u003c/span\u003e neutrophil activation in TB \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. In this study, we demonstrated that CD177\u003csup\u003e+\u003c/sup\u003e granulocytes expressed high levels of CD66b and low levels of PD1. Additionally, the MFI of CD177 in the LDG was significantly higher than that in the NDG of the TB patients, and the percentage and MFI of CD66b and PD1 on CD177\u003csup\u003e+\u003c/sup\u003e LDG was higher than those on CD177\u003csup\u003e+\u003c/sup\u003e ND\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eG\u003c/span\u003e. Moreover, CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG was associated with CD66b, PD1, and CFP-10 sfc in TB patients and showed good performance in distinguishing between TB and HC, PTB and EPTB. Our findings, for the first time, revealed the pathogenic neutrophil subsets, namely CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG, may serve as diagnostic biomarker\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003es\u003c/span\u003e of TB.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eCD177⁺ LDG\u003c/span\u003e expressed significantly more CD66b (specific granules) than CD177⁺ NDG, which suggested a possible dominant degranulation property of CD177⁺ LDG. There were notable associations observed between the CD177 MFI on LDG and CD66b MFI, along with CFP-10 sfc, which reinforced the notion that CD177⁺ LDG may possess pro-inflammatory characteristics in an activated state. Consistent with its pro-inflammatory characteristics, the expression of CD177, a specific neutrophil activation marker, has been reported to contribute to predict the severity and mortality at COVID-19 the gene and protein level\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003es\u003c/span\u003e \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. This also supports the observation that TB involves an imbalance in granulocyte subsets and that the abnormal expression of key signaling molecules on neutrophils plays an important role in TB pathogenesis \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Interest\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eingly, a previous study revealed that CD177\u003c/span\u003e\u003csup\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003epos\u003c/span\u003e\u003c/sup\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eneutrophils exhibited\u003c/span\u003e reduced secretion of pro-inflammatory cytokines but elevated production of IL-22 and transforming growth factor-β (TGF-β) \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e in inflammatory bowel disease (IBD). Moreover, CD177\u003csup\u003e+\u003c/sup\u003e neutrophils exhibit enhanced ability to produce NETs and contribute to organ damage \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eduring heatstroke\u003c/span\u003e\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. In addition, the proportion of CD177-positive neutrophils is increased in the hepatic tissues of patients with biliary atresia, and the expression levels of IFN \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand degranulation-related genes were elevated in\u003c/span\u003e CD177-positive neutrophils\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. These findings strengthen the advantage of utilizing CD177 as a pro-inflammatory biomarker in patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewith TB\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eFinally, we conducted roc to anaylze the performance of the CD177\u003csup\u003e+\u003c/sup\u003egranulocytes and found the percentage of CD177\u003csup\u003e+\u003c/sup\u003e NDG showed \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e90.00% sensitivity and 59.26% specificity\u003c/span\u003e with an AUC of 0.748 in distinguishing between patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewith TB and HC\u003c/span\u003e, followed by \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe MFI of CD177 of LDG.\u003c/span\u003e Notably, MFI of PD1 on CD177\u003csup\u003e+\u003c/sup\u003e LDG harbored the highest AUC to differentiate EPTB and PTB (AUC\u0026thinsp;=\u0026thinsp;0.818 ) with 70.00% sensitivity and 88.24% specificity, which strengthed that CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG could serve as diagnostic biomarker\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003es\u003c/span\u003e of TB.\u003c/p\u003e\u003cp\u003eOur study had several limitations. First, this was a single-center study and the observed association between CD177\u003csup\u003e+\u003c/sup\u003e granulocytes and TB requires large sample size study for validation in a multic\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eenter cohort\u003c/span\u003e. Second, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eadditional mechanistic investigations are needed to better understand the role of CD177 in granulocyte migration, cytokine release, and T-cell suppression\u003c/span\u003e in TB in the cellular or animal level. Future research can describe the expression characteristics and biological significance of CD177 in granulocyte subsets more accurately through large-scale clinical sample analysis and single-cell RNA sequencing technology.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur study revealed t\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ehe\u003c/span\u003e MFI of CD177 on LDG was significantly increased, and the percentage of CD177\u003csup\u003e+\u003c/sup\u003e NDG was decreased in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe TB group\u003c/span\u003e compared to that in the HC \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003egroup, as determined by flow\u003c/span\u003e cytometry. CD177⁺ LDG are characterized by high CD66b and low PD1, and showed a certain correlation with CD66b and CFP \u0026minus;\u0026thinsp;10 sfc. Their strong diagnostic performance in TB and HC, PTB and EPTB supported their potential as reliable diagnostic biomarkers. Our research established \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eROC to distinguish TB and HC, PTB and EPTB\u003c/span\u003e, which might improve our understanding of the role of CD177\u003csup\u003e+\u003c/sup\u003e granulocytes in TB.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNDG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enormal density granulocytes\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLDG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elow density granulocytes\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ereceiver operating characteristic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eplatelet count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eneutrophil-to-lymphocyte ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTNF-α\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etumor necrosis factor-α\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCFP-10 SFC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eculture filtrate protein 10 spot-forming cells\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIFN-γ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003einterferon-γ\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMtb\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMycobacterium tuberculosis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTuberculosis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNETs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eneutrophil extracellular traps\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePTB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epulmonary tuberculosis patients\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIL: interleukin\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIL-1β\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterleukin-1 beta\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePBMC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eperipheral blood mononuclear cells\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehealthy controls\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eARDS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eacute respiratory distress syndrome\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eATB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eactive tuberculosis patients\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLTBI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elatent tuberculosis infections\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eESAT-6 sfc\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEarly secretory antigenic target 6 spot-forming cells\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTBAg\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMtb-specific antigens\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePHA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ephytohemagglutinin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eESR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eerythrocyte sedimentation rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-reactive protein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ewhite blood cell count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ered blood cell count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eplatelet count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHCT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehematocrit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehemoglobin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elymphocyte count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eL%\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elymphocyte percentage\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emonocyte count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eM%\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emonocyte percentage\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eneutrophil count\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eN%\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eneutrophil percentage\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elymphocyte-to-monocyte ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eneutrophil-to-lymphocyte ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003edNLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ederived NLR\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eplatelet-to-lymphocyte ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSII\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003esystemic immune inflammation index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eplatelet to monocyte ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMNR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emonocyte to neutrophil ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePNR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eplatelet to neutrophil ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIGRA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003einterferon-gamma release assays\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ephycoerythrin-Cyanin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eECD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ephycoerythrin-Texas Red tandem\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFITC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003efluorescein isothiocyanate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ephycoerythrin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePD-1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProgrammed Death receptor 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMFI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emean fluorescence intensity\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003einterquartile range\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ethe area under the curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEPTB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eextrapulmonary tuberculosis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eG-CSF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003egranulocyte-colony stimulating factor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSLE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eindividuals with systemic lupus erythematosus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAASV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eANCA-associated systemic vasculitis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epolycythemia vera\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTGF-β\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etransforming growth factor-β\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIBD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003einflammatory bowel disease.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and informed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the Medical Ethical Committees of the First Affiliated Hospital of Nanchang University [approval no. (2024)CDYFYYLK(07-046)]. Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the listed authors have carefully reviewed and approved this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions of this study are included in the article and supplementary material. Further inquiries can be directed toward the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFounding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Education Department of Jiangxi Province (GJJ2200216); Natural Science Foundation of Jiangxi province(20212BAB216028).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding acquisition: Xue Li, Zai chuan Lin and Rigu Su; Funding acquisition: Xue Li; Investigation, Zai chuan Lin; Project administration: Xue Li, Zikun Huang, and Junming Li; Resources: Jun Liu; Software: Qing Luo; Supervision: Qing Luo; Validation: Xue Li and Zai chuan Lin; Visualization: Rigu Su; Writing – original draft: Xue Li and Zai chuan Lin; Writing – review and editing: Zikun Huang and Junming Li.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGarg T, Rath G, Murthy RR, Gupta UD, Vatsala PG, Goyal AK. 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Identification of CD177 as the most dysregulated parameter in a microarray study of purified neutrophils from septic shock patients. \u003cem\u003eImmunology letters\u003c/em\u003e. \u003cstrong\u003e2016\u003c/strong\u003e; 178:122\u0026ndash;130.\u003c/li\u003e\n \u003cli\u003eXie, Q., Klesney-Tait, J., Keck, K., Parlet, C., Borcherding, N., Kolb, R., Li, W., Tygrett, L., Waldschmidt, T., Olivier, A., Chen, S., Liu, G. H., Li, X., \u0026amp; Zhang, W. Characterization of a novel mouse model with genetic deletion of CD177. \u003cem\u003eProtein \u0026amp; cell\u003c/em\u003e. \u003cstrong\u003e2015\u003c/strong\u003e; 6(2), 117\u0026ndash;126.\u003c/li\u003e\n \u003cli\u003eGeng, X., Wu, X., Yang, Q., Xin, H., Zhang, B., Wang, D., Liu, L., Liu, S., Chen, Q., Liu, Z., Zhang, M., Pan, S., Zhang, X., Gao, L., \u0026amp; Jin, Q. Whole transcriptome sequencing reveals neutrophils\u0026apos; transcriptional landscape associated with active tuberculosis. \u003cem\u003eFrontiers in immunology\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e; 13, 954221.\u003c/li\u003e\n \u003cli\u003eEsterhuyse, M. M., Weiner, J., 3rd, Caron, E., Loxton, A. G., Iannaccone, M., Wagman, C., Saikali, P., Stanley, K., Wolski, W. E., Mollenkopf, H. J., Schick, M., Aebersold, R., Linhart, H., Walzl, G., \u0026amp; Kaufmann, S. H. Epigenetics and Proteomics Join Transcriptomics in the Quest for Tuberculosis Biomarkers. \u003cem\u003emBio\u003c/em\u003e. \u003cstrong\u003e2015\u003c/strong\u003e; 6(5): e01187-15.\u003c/li\u003e\n \u003cli\u003eLa Manna, M. P., Orlando, V., Paraboschi, E. M., Tamburini, B., Di Carlo, P., Cascio, A., Asselta, R., Dieli, F., \u0026amp; Caccamo, N. Mycobacterium tuberculosis Drives Expansion of Low-Density Neutrophils Equipped With Regulatory Activities. \u003cem\u003eFrontiers in immunology\u003c/em\u003e.\u003cstrong\u003e\u0026nbsp;2019\u003c/strong\u003e; 10, 2761.\u003c/li\u003e\n \u003cli\u003eBloom, C. I., Graham, C. M., Berry, M. P., Rozakeas, F., Redford, P. S., Wang, Y., Xu, Z., Wilkinson, K. A., Wilkinson, R. J., Kendrick, Y., Devouassoux, G., Ferry, T., Miyara, M., Bouvry, D., Valeyre, D., Gorochov, G., Blankenship, D., Saadatian, M., Vanhems, P., Beynon, H., \u0026hellip; O\u0026apos;Garra, A. Transcriptional blood signatures distinguish pulmonary tuberculosis, pulmonary sarcoidosis, pneumonias and lung cancers.\u003cem\u003e\u0026nbsp;PloS one\u003c/em\u003e.\u003cstrong\u003e\u0026nbsp;2013\u003c/strong\u003e; 8(8), e70630.\u003c/li\u003e\n \u003cli\u003eCaruccio L, Bettinotti M, Matsuo K, Sharon V, Stroncek D. Expression of human neutrophil antigen-2a (NB1) is increased in pregnancy. \u003cem\u003eTransfusion\u003c/em\u003e. \u003cstrong\u003e2003\u003c/strong\u003e; 43(3): 357-363.\u003c/li\u003e\n \u003cli\u003eTemerinac, S., Klippel, S., Strunck, E., R\u0026ouml;der, S., L\u0026uuml;bbert, M., Lange, W., Azemar, M., Meinhardt, G., Schaefer, H. E., \u0026amp; Pahl, H. L. Cloning of PRV-1, a novel member of the uPAR receptor superfamily, which is overexpressed in polycythemia rubra vera. \u003cem\u003eBlood\u003c/em\u003e. \u003cstrong\u003e2000\u003c/strong\u003e; 95(8):2569-2576.\u003c/li\u003e\n \u003cli\u003eG\u0026ouml;hring K, Wolff J, Doppl W, Schmidt KL, Fenchel K, Pralle H, Sibelius U, Bux J. Neutrophil CD177 (NB1 gp, HNA-2a) expression is increased in severe bacterial infections and polycythaemia vera. \u003cem\u003eBr J Haematol.\u003c/em\u003e \u003cstrong\u003e2004\u003c/strong\u003e; 126(2):252\u0026ndash;254.\u003c/li\u003e\n \u003cli\u003eZhou, G., Yu, L., Fang, L., Yang, W., Yu, T., Miao, Y., Chen, M., Wu, K., Chen, F., Cong, Y., \u0026amp; Liu, Z. CD177\u003csup\u003e+\u003c/sup\u003e neutrophils as functionally activated neutrophils negatively regulate IBD. \u003cem\u003eGut\u003c/em\u003e. \u003cstrong\u003e2018\u003c/strong\u003e; 67(6):1052\u0026ndash;1063.\u003c/li\u003e\n \u003cli\u003eWang F, Zhang Y, Sun M, Li M, Wang Y, Zhang D, Yao S. Single-cell sequencing reveals the same heterogeneity of neutrophils in heatstroke-induced lung and liver injury. \u003cem\u003eMucosal Immunol\u003c/em\u003e. \u003cstrong\u003e2025;\u003c/strong\u003e 18(3):742\u0026ndash;756.\u003c/li\u003e\n \u003cli\u003eDahlstrand Rudin A, Amirbeagi F, Davidsson L, Khamzeh A, Thorbert Mros S, Thulin P, Welin A, Bj\u0026ouml;rkman L, Christenson K, Bylund J. The neutrophil subset defined by CD177 expression is preferentially recruited to gingival crevicular fluid in periodontitis. \u003cem\u003eJ Leukoc Biol\u003c/em\u003e. \u003cstrong\u003e2021\u003c/strong\u003e; 109(2): 349\u0026ndash;362.\u003c/li\u003e\n \u003cli\u003eSaha, R., Pradhan, S. S., Shalimar, Das, P., Mishra, P., Singh, R., Sivaramakrishnan, V., \u0026amp; Acharya, P. Inflammatory signature in acute-on-chronic liver failure includes increased expression of granulocyte genes ELANE, MPO and CD177. \u003cem\u003eScientific reports\u003c/em\u003e. \u003cstrong\u003e2021\u003c/strong\u003e; 11(1): 18849.\u003c/li\u003e\n \u003cli\u003eSeo, D. H., Che, X., Kim, S., Kim, D. H., Ma, H. W., Kim, J. H., Kim, T. I., Kim, W. H., Kim, S. W., \u0026amp; Cheon, J. H. Triggering Receptor Expressed on Myeloid Cells-1 Agonist Regulates Intestinal Inflammation via Cd177\u003csup\u003e+\u003c/sup\u003e Neutrophils.\u003cem\u003e\u0026nbsp;Frontiers in immunology\u003c/em\u003e. \u003cstrong\u003e2021\u003c/strong\u003e; 12, 650864.\u003c/li\u003e\n \u003cli\u003eWu, J., Gao, P., Yang, C., Zhuang, F., Luo, Y., Wen, F., Zhang, P., Wang, L., Xie, H., Dai, C., Zhao, D., Li, C., Deng, H., Deng, Z., \u0026amp; Chen, C. Targeting mitochondrial complex I of CD177 neutrophils alleviates lung ischemia-reperfusion injury. Cell reports. \u003cem\u003eMedicine\u003c/em\u003e. \u003cstrong\u003e2025\u003c/strong\u003e; 6(5), 102140.\u003c/li\u003e\n \u003cli\u003eChen, H., Wu, X., Sun, R., Lu, H., Lin, R., Gao, X., Li, G., Feng, Z., Zhu, R., Yao, Y., Feng, B., \u0026amp; Liu, Z. Dysregulation of CD177 neutrophils on intraepithelial lymphocytes exacerbates gut inflammation via decreasing microbiota-derived DMF. \u003cem\u003eGut microbes\u003c/em\u003e. \u003cstrong\u003e2023\u003c/strong\u003e; 15(1), 2172668.\u003c/li\u003e\n \u003cli\u003eKuroki M, Yamanaka T, Matsuo Y, Oikawa S, Nakazato H, Matsuoka Y. Immunochemical analysis of carcinoembryonic antigen (CEA)-related antigens differentially localized in intracellular granules of human neutrophils. \u003cem\u003eImmunol Invest\u003c/em\u003e. \u003cstrong\u003e1995\u003c/strong\u003e; 24:829\u0026ndash;43.\u003c/li\u003e\n \u003cli\u003eL\u0026eacute;vy, Y., Wiedemann, A., Hejblum, B. P., Durand, M., Lefebvre, C., Sur\u0026eacute;naud, M., Lacabaratz, C., Perreau, M., Foucat, E., D\u0026eacute;chenaud, M., Tisserand, P., Blengio, F., Hivert, B., Gauthier, M., Cervantes-Gonzalez, M., Bachelet, D., Laou\u0026eacute;nan, C., Bouadma, L., Timsit, J. F., Yazdanpanah, Y., French COVID cohort study group. CD177, a specific marker of neutrophil activation, is associated with coronavirus disease 2019 severity and death. \u003cem\u003eiScience\u003c/em\u003e. \u003cstrong\u003e2021\u003c/strong\u003e;24(7):102711.\u003c/li\u003e\n \u003cli\u003eHuang C, Fan X, Shen Y, Shen M, Yang L. Neutrophil subsets in noncancer liver diseases: Cellular crosstalk and therapeutic targets. \u003cem\u003eEur J Immunol\u003c/em\u003e. \u003cstrong\u003e202\u003c/strong\u003e3;53(9):e2250324.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographic information and characteristics of TB patients and healthy controls.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"575\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003e\u003cstrong\u003echaracteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/strong\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eGender, male, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e23 (33.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e17 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eAge, mean \u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e50.79 \u0026plusmn; 17.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e49.77 \u0026plusmn; 17.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eDistribution sites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eLungs, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e23 (54.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eIntestine, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e4 (9.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eLumbar spine, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e4 (9.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eLymph nodes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e3 (7.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eCervical spine, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e2 (4.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eAbdominal cavity, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e2 (4.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003ePleura, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e2 (4.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eSpine, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1 (2.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eEsophage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1 (2.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eClinical features\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eCoughing phlegm, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e9 (21.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003ePain, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e8 (190%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eFever, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e4 (9.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eChest tightness, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e3 (7.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eRash, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1 (2.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eNumbness, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1 (2.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eDiarrhea, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1 (2.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eFatigue, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1 (2.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eExperimental data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eESR, mean \u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e38.29 \u0026plusmn; 32.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eCRP, mean \u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e18.17 \u0026plusmn; 31.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eT-spot, positive, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e24 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eWBC, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e5.4 (4.63, 6.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e6.09 (5.07, 7.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.354\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eRBC, mean \u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e4.44 \u0026plusmn; 0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e4.82 \u0026plusmn; 0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eHB, mean \u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e128.67 \u0026plusmn; 21.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e147.75 \u0026plusmn; 14.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eHCT, mean \u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e0.39 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e43.59 \u0026plusmn; 3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003ePLT, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e201.5 (172, 262)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e232 (203.75, 270.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eL, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1.185 (0.96, 1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e2.105 (1.74, 2.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eM, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e0.40351 (0.29, 0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.425 (0.37, 0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eN, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e3.28 (2.99, 4.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e3.285 (2.52, 3.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eLMR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e2.3901 (1.61, 4.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e1.543 (1.29, 1.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eNLR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e285.47 (172.86, 404.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e464.14 (362.62, 737.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003edNLR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e1.856 (1.35, 2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e1.1972 (1.03, 1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003ePLR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e0.5058 (0.32, 0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.8998 (0.69, 1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eSII, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e497.93 (284.66, 1033.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e345.88 (299.73, 459.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003ePMR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e530.51 (371.70, 805.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e540.95 (485.37, 649.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003eMNR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e0.11 (0.08, 0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.1325 (0.11, 0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003ePNR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e59.472 (51.57, 77.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e76.475 (59.91, 90.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 575px;\"\u003e\n \u003cp\u003eAbbreviations:TB: tuberculosis, HC: healthy controls, ESR: erythrocyte sedimentation rate, CRP: C-reactive protein, T-spot: T Cell Spot Test, WBC:white blood cell count, IQR: interquartile range, RBC: red blood cell count, PLT: platelet count, HCT: hematocrit, HB: hemoglobin, L: lymphocyte count, M: monocyte count, N: neutrophil count, LMR: lymphocyte-to-monocyte ratio, NLR: neutrophil-to-lymphocyte ratio, dNLR: derived NLR, PLR: platelet-to-lymphocyte ratio, SII: systemic immune inflammation index, PMR: platelet to monocyte ratio, MNR: monocyte to neutrophil ratio, PNR: platelet to neutrophil ratio.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 575px;\"\u003e\n \u003cp\u003e*P value for TB group and HC group, ***: p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Tuberculosis, neutrophils, LDG, CD177, diagnostic","lastPublishedDoi":"10.21203/rs.3.rs-7809533/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7809533/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eGranulocyte subsets, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003esuch as normal\u003c/span\u003e-density granulocytes(NDG) and low-density granulocytes(LDG), \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eplay an important role in the pathogenesis of tuberculosis (TB).\u003c/span\u003e CD177\u003csup\u003e+\u003c/sup\u003e neutrophils were up-regulated during inflammation and \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003etumour. H\u003c/span\u003eowever, the role of CD177 of neutrophils in TB patients remain elusive. This study aimed to explore the expression of CD177\u003csup\u003e+\u003c/sup\u003e\u0026thinsp;neutrophils in TB patients and assess the correlation between CD177 and clinical characteristics to determine the expression and diagnostic value of CD177\u003csup\u003e+\u003c/sup\u003e neutrophils of tuberculosis patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThe expression of CD177 of LDG and NDG were confirmed by flow cytometry in 42 \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eTB\u003c/span\u003e patients and 26 healthy controls. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe\u003c/span\u003e levels of markers related to granulocyte activation(CD66b) and immunosuppression programmed death receptor 1 (\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ePD1)\u003c/span\u003e in CD177\u003csup\u003e+\u003c/sup\u003e LDG and CD177\u003csup\u003e+\u003c/sup\u003e NDG were compared in 27 \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eTB\u003c/span\u003e patients. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe levels of\u003c/span\u003e IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, TNF-α, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand\u003c/span\u003e IFN-γ were measured with cytokine profiling kits. Correlations with clinical characteristics, inflammatory markers and cytokines as well as receiver operating characteristic (ROC) curve analysis were determined.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eFlow cytometry analysis confirmed \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe elevated CD177\u003c/span\u003e\u003csup\u003e+\u003c/sup\u003e LDG and low \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eCD177\u003c/span\u003e\u003csup\u003e+\u003c/sup\u003e NDG \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eexpression in TB\u003c/span\u003e patients compared with healthy controls. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eCD177\u003c/span\u003e\u003csup\u003e+\u003c/sup\u003e LDG was characterized by high CD66b and low PD-1 expression and was significant\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ely correlat\u003c/span\u003eed with CD66b and culture filtrate protein 10 spot-forming cells (CFP-10 SFC), and CD177\u003csup\u003e+\u003c/sup\u003e NDG is associated with PD1. In addition, the percentage of CD177\u003csup\u003e+\u003c/sup\u003e LDG, the percentage of PD1 of CD177\u003csup\u003e+\u003c/sup\u003e LDG, and MFI of PD1 of CD177\u003csup\u003e+\u003c/sup\u003e LDG were all significantly increased in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe EPTB group\u003c/span\u003e compared to \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe PTB group. T\u003c/span\u003ehe percentage of CD177\u003csup\u003e+\u003c/sup\u003e NDG showed \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e90.00% sensitivity and 59.26% specificity\u003c/span\u003e with an AUC of 0.748 in distinguishing between patients \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewith TB and HC\u003c/span\u003e, followed by \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe MFI of CD177 of LDG.\u003c/span\u003e Notably, MFI of PD1 on CD177\u003csup\u003e+\u003c/sup\u003e LDG harbored the highest AUCs to differentiate EPTB and PTB with 70.00% sensitivity and 88.24% specificity(AUC\u0026thinsp;=\u0026thinsp;0.818 ). \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThese findings underscore the role of CD177 in\u003c/span\u003e granulocyte subsets of TB.\u003c/p\u003e","manuscriptTitle":"Exploring the expression and diagnostic value of CD177 + neutrophils in tuberculosis patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-10 10:24:51","doi":"10.21203/rs.3.rs-7809533/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fb3acbb0-279e-4228-b9e2-f4d33652b58d","owner":[],"postedDate":"November 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T06:24:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-10 10:24:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7809533","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7809533","identity":"rs-7809533","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}