Sepsis diagnosis and treatment: recent advances in the detection of pathogen and host immune status_West China Medical Journal

Authors：

YE Rui ¹ , WANG Chi ^1,2,3 , DING Fei ^1,2,3 , HE Yong ^1,2,3 ,  NIE Xin ^1,2,3

1. Department of Laboratory Medicine, West China Hospital / Department of Medical Laboratory Medicine, West China School of Medicine, Sichuan University, Chengdu, Sichuan 610041, P. R China;
2. Clinical Laboratory Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R China;
3. Sichuan Clinical Research Center for Laboratory Medicine, Chengdu, Sichuan 610041, P. R China;

Corresponding author：

NIE Xin, Email: niexinscu@scu.edu.cn

Keywords：

Sepsis; early diagnosis; microbiological techniques; immunologic monitoring; biomarker

DOI：

10.7507/1002-0179.202507235

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Sepsis is a systemic inflammatory response syndrome caused by infection, with high fatality rate and complex pathogenesis. Early and accurate diagnosis is essential to improving the prognosis of patients with sepsis. This review briefly describes the basic pathogenesis of sepsis, and summarizes the current new technologies for detecting sepsis from two aspects: pathogen detection and host immune status detection, such as digital polymerase chain reaction, biosensors, fluorescent probes, single-cell RNA sequencing, and enzyme-linked immunospot assay. By comprehensively analyzing and applying these new techniques, it is helpful to improve the efficiency and accuracy of early diagnosis of sepsis and improve the clinical treatment effect of patients.

Citation： YE Rui, WANG Chi, DING Fei, HE Yong, NIE Xin. Sepsis diagnosis and treatment: recent advances in the detection of pathogen and host immune status. West China Medical Journal, 2025, 40(8): 1317-1322. doi: 10.7507/1002-0179.202507235 Copy

1.	Yuki K, Koutsogiannaki S. Pattern recognition receptors as therapeutic targets for bacterial, viral and fungal sepsis. Int Immunopharmacol, 2021, 98: 107909.
2.	Ren ZY, Wang XR, Jia BQ, et al. Nanozyme-energized SERS sensor for ultrasensitive dual-mode bacterial detection. Acs Applied Nano Materials, 2025, 8(16): 8385-8396.
3.	Xu JQ, Zhang WY, Fu JJ, et al. Viral sepsis: diagnosis, clinical features, pathogenesis, and clinical considerations. Mil Med Res, 2024, 11(1): 78.
4.	Zhou Y, Zhang W, Cheng S, et al. Flexible PDMS-SERS platform for culture-free diagnosis of bacterial infections in clinical wound care. Talanta, 2025, 293: 128089.
5.	Wu MY, Chen L, Chen Q, et al. Engineered phage with aggregation-induced emission photosensitizer in cocktail therapy against sepsis. Adv Mater, 2023, 35(6): e2208578.
6.	Cross D, Drury R, Hill J, et al. Epigenetics in sepsis: understanding its role in endothelial dysfunction, immunosuppression, and potential therapeutics. Front Immunol, 2019, 10: 1363.
7.	Scicluna BP, van Vught LA, Zwinderman AH, et al. Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study. Lancet Respir Med, 2017, 5(10): 816-826.
8.	Saxena J, Das S, Kumar A, et al. Biomarkers in sepsis. Clin Chim Acta, 2024, 562: 119891.
9.	Yao RQ, Ren C, Zheng LY, et al. Advances in immune monitoring approaches for sepsis-induced immunosuppression. Front Immunol, 2022, 13: 891024.
10.	Barichello T, Generoso JS, Singer M, et al. Biomarkers for sepsis: more than just fever and leukocytosis-a narrative review. Crit Care, 2022, 26(1): 14.
11.	He RR, Yue GL, Dong ML, et al. Sepsis biomarkers: advancements and clinical applications: a narrative review. Int J Mol Sci, 2024, 25(16): 9010.
12.	Li F, Wang S, Gao Z, et al. Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring. Front Med (Lausanne), 2025, 11: 1510792.
13.	Torres LK, Pickkers P, van der Poll T. Sepsis-induced immunosuppression. Annu Rev Physiol, 2022, 84: 157-181.
14.	Liu D, Huang SY, Sun JH, et al. Sepsis-induced immunosuppression: mechanisms, diagnosis and current treatment options. Mil Med Res, 2022, 9(1): 56.
15.	Yang J, Li H. The impact of aging and COVID-19 on our immune system: a high-resolution map from single cell analysis. Protein Cell, 2020, 11(10): 703-706.
16.	Netea MG, Schlitzer A, Placek K, et al. Innate and adaptive immune memory: an evolutionary continuum in the host’s response to pathogens. Cell Host Microbe, 2019, 25(1): 13-26.
17.	Zindel J, Kubes P. DAMPs, PAMPs, and LAMPs in immunity and sterile inflammation. Annu Rev Pathol, 2020, 15: 493-518.
18.	Li D, Wu M. Pattern recognition receptors in health and diseases. Signal Transduct Target Ther, 2021, 6(1): 291.
19.	Broz P, Monack DM. Newly described pattern recognition receptors team up against intracellular pathogens. Nat Rev Immunol, 2013, 13(8): 551-565.
20.	Kufer TA, Creagh EM, Bryant CE. Guardians of the cell: effector-triggered immunity steers mammalian immune defense. Trends Immunol, 2019, 40(10): 939-951.
21.	Gong T, Liu L, Jiang W, et al. DAMP-sensing receptors in sterile inflammation and inflammatory diseases. Nat Rev Immunol, 2020, 20(2): 95-112.
22.	Wang X, Xia Z, Wang H, et al. Cell-membrane-coated nanoparticles for the fight against pathogenic bacteria, toxins, and inflammatory cytokines associated with sepsis. Theranostics, 2023, 13(10): 3224-3244.
23.	Li Y, Zhang H, Chen C, et al. Biomimetic immunosuppressive exosomes that inhibit cytokine storms contribute to the alleviation of sepsis. Adv Mater, 2022, 34(19): e2108476.
24.	Li Y, Yu J, Zeng Z, et al. Regulation of ubiquitination in sepsis: from PAMP versus DAMP to peripheral inflammation and cell death. Front Immunol, 2024, 15: 1513206.
25.	Jiang Y, Gao S, Chen Z, et al. Pyroptosis in septic lung injury: interactions with other types of cell death. Biomed Pharmacother, 2023, 169: 115914.
26.	Lazzaro A, De Girolamo G, Filippi V, et al. The interplay between host defense, infection, and clinical status in septic patients: a narrative review. Int J Mol Sci, 2022, 23(2): 803.
27.	Azoulay E, Zuber J, Bousfiha AA, et al. Complement system activation: bridging physiology, pathophysiology, and therapy. Intensive Care Med, 2024, 50(11): 1791-1803.
28.	de Nooijer AH, Kotsaki A, Kranidioti E, et al. Complement activation in severely ill patients with sepsis: no relationship with inflammation and disease severity. Crit Care, 2023, 27(1): 63.
29.	Reis ES, Mastellos DC, Hajishengallis G, et al. New insights into the immune functions of complement. Nat Rev Immunol, 2019, 19(8): 503-516.
30.	Chen S, Wu A, Shen X, et al. Disrupting the dangerous alliance: dual anti-inflammatory and anticoagulant strategy targets platelet-neutrophil crosstalk in sepsis. J Control Release, 2025, 379: 814-831.
31.	Scully M, Levi M. How we manage haemostasis during sepsis. Br J Haematol, 2019, 185(2): 209-218.
32.	Hernández-Jiménez E, Plata-Menchaca EP, Berbel D, et al. Assessing sepsis-induced immunosuppression to predict positive blood cultures. Front Immunol, 2024, 15: 1447523.
33.	Cao C, Yu M, Chai Y. Pathological alteration and therapeutic implications of sepsis-induced immune cell apoptosis. Cell Death Dis, 2019, 10(10): 782.
34.	Zheng LY, Duan Y, He PY, et al. Dysregulated dendritic cells in sepsis: functional impairment and regulated cell death. Cell Mol Biol Lett, 2024, 29(1): 81.
35.	Gao X, Cai S, Li X, et al. Sepsis-induced immunosuppression: mechanisms, biomarkers and immunotherapy. Front Immunol, 2025, 16: 1577105.
36.	Islam MM, Watanabe E, Salma U, et al. Immunoadjuvant therapy in the regulation of cell death in sepsis: recent advances and future directions. Front Immunol, 2024, 15: 1493214.
37.	Molinaro R, Pastò A, Corbo C, et al. Macrophage-derived nanovesicles exert intrinsic anti-inflammatory properties and prolong survival in sepsis through a direct interaction with macrophages. Nanoscale, 2019, 11(28): 13576-13586.
38.	Sehgal R, Maiwall R, Rajan V, et al. Granulocyte-macrophage colony-stimulating factor modulates myeloid-derived suppressor cells and treg activity in decompensated cirrhotic patients with sepsis. Front Immunol, 2022, 13: 828949.
39.	Joshi I, Carney WP, Rock EP. Utility of monocyte HLA-DR and rationale for therapeutic GM-CSF in sepsis immunoparalysis. Front Immunol, 2023, 14: 1130214.
40.	Lei S, Chen S, Zhong Q. Digital PCR for accurate quantification of pathogens: principles, applications, challenges and future prospects. Int J Biol Macromol, 2021, 184: 750-759.
41.	Hou Y, Chen S, Zheng Y, et al. Droplet-based digital PCR (ddPCR) and its applications. Trac-Trends Anal. Chem, 2023, 158: 116897.
42.	Wouters Y, Dalloyaux D, Christenhusz A, et al. Droplet digital polymerase chain reaction for rapid broad-spectrum detection of bloodstream infections. Microb Biotechnol, 2020, 13(3): 657-668.
43.	Wu J, Tang B, Qiu Y, et al. Clinical validation of a multiplex droplet digital PCR for diagnosing suspected bloodstream infections in ICU practice: a promising diagnostic tool. Crit Care, 2022, 26(1): 243.
44.	Park J, Lee KG, Han DH, et al. Pushbutton-activated microfluidic dropenser for droplet digital PCR. Biosens Bioelectron, 2021, 181: 113159.
45.	Pan F, Altenried S, Scheibler S, et al. Ultrafast determination of antimicrobial resistant Staphylococcus aureus specifically captured by functionalized magnetic nanoclusters. ACS Sens, 2022, 7(11): 3491-3500.
46.	Shrivastava S, Arya R, Kim KK, et al. A quorum-based fluorescent probe for imaging pathogenic bacteria. J Mater Chem B, 2022, 10(23): 4491-4500.
47.	Zhao J, Li Y, Chen X, et al. Sensitive NIR fluorescence identification of bacteria in whole blood with bioorthogonal nanoprobes for early sepsis diagnosis. Anal Chem, 2023, 95(2): 955-965.
48.	Liu X, Chen X, Yin S, et al. Dual-modal detection of antimicrobial susceptibility in pathogenic bacteria based on the high-throughput microfluidic platform. Chem Eng J, 2024, 499: 156506.
49.	Zhou WM, Yan YY, Guo QR, et al. Microfluidics applications for high-throughput single cell sequencing. J Nanobiotechnology, 2021, 19(1): 312.
50.	Saviano A, Henderson NC, Baumert TF. Single-cell genomics and spatial transcriptomics: discovery of novel cell states and cellular interactions in liver physiology and disease biology. J Hepatol, 2020, 73(5): 1219-1230.
51.	Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol, 2018, 18(1): 35-45.
52.	Yao RQ, Li ZX, Wang LX, et al. Single-cell transcriptome profiling of the immune space-time landscape reveals dendritic cell regulatory program in polymicrobial sepsis. Theranostics, 2022, 12(10): 4606-4628.
53.	Liu Y, Li W, Lei L, et al. Effects of PGK1 on immunoinfiltration by integrated single-cell and bulk RNA-sequencing analysis in sepsis. Front Immunol, 2024, 15: 1449975.
54.	Balch JA, Chen UI, Liesenfeld O, et al. Defining critical illness using immunological endotypes in patients with and without sepsis: a cohort study. Crit Care, 2023, 27(1): 292.
55.	Komorowski M, Green A, Tatham KC, et al. Sepsis biomarkers and diagnostic tools with a focus on machine learning. EBioMedicine, 2022, 86: 104394.
56.	Fu X, Ma W, Zuo Q, et al. Application of machine learning for high-throughput tumor marker screening. Life Sci, 2024, 348: 122634.
57.	Zhang WY, Chen ZH, An XX, et al. Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning. World J Pediatr, 2023, 19(11): 1094-1103.
58.	Baghela A, Pena OM, Lee AH, et al. Predicting sepsis severity at first clinical presentation: the role of endotypes and mechanistic signatures. EBioMedicine, 2022, 75: 103776.
59.	Rajkomar A, Oren E, Chen K, et al. Scalable and accurate deep learning with electronic health records. NPJ Digit Med, 2018, 1: 18.
60.	Prithula J, Islam KR, Kumar J, et al. A novel classical machine learning framework for early sepsis prediction using electronic health record data from ICU patients. Comput Biol Med, 2025, 184: 109284.
61.	Barrios EL, Mazer MB, McGonagill PW, et al. Adverse outcomes and an immunosuppressed endotype in septic patients with reduced IFN-γ ELISpot. JCI Insight, 2024, 9(2): e175785.
62.	Price AD, Becker ER, Barrios EL, et al. Surviving septic patients endotyped with a functional assay demonstrate active immune responses. Front Immunol, 2024, 15: 1418613.
63.	Barrios EL, Balzano-Nogueira L, Polcz VE, et al. Unique lymphocyte transcriptomic profiles in septic patients with chronic critical illness. Front Immunol, 2024, 15: 1478471.
64.	Bonavia AS, Samuelsen A, Chroneos ZC, et al. Comparison of rapid cytokine immunoassays for functional immune phenotyping. Front Immunol, 2022, 13: 940030.
65.	Liu S, Lu F, Chen S, et al. Graphene oxide-based fluorescent biosensors for pathogenic bacteria detection: a review. Anal Chim Acta, 2025, 1337: 343428.
66.	Ghorbani F, Abbaszadeh H, Mehdizadeh A, et al. Biosensors and nanobiosensors for rapid detection of autoimmune diseases: a review. Mikrochim Acta, 2019, 186(12): 838.
67.	Wang Y, Guan M, Mi F, et al. Combining multisite functionalized magnetic nanomaterials with interference-free SERS nanotags for multi-target sepsis biomarker detection. Anal Chim Acta, 2023, 1272: 341523.
68.	Guo R, Wang J, Zhao W, et al. A novel strategy for specific sensing and inactivation of Escherichia coli: constructing a targeted sandwich-type biosensor with multiple SERS hotspots to enhance SERS detection sensitivity and near-infrared light-triggered photothermal sterilization performance. Talanta, 2024, 269: 125466.
69.	Wang C, Xu G, Wang W, et al. Bioinspired hot-spot engineering strategy towards ultrasensitive SERS sandwich biosensor for bacterial detection. Biosens Bioelectron, 2023, 237: 115497.
70.	Lu TC, Yang YJ, Zhong Y, et al. Simultaneous detection of C-reactive protein and lipopolysaccharide based on a dual-channel electrochemical biosensor for rapid Gram-typing of bacterial sepsis. Biosens Bioelectron, 2024, 243: 115772.
71.	Kim WH, Lee S, Jeon MJ, et al. Rapid and differential diagnosis of sepsis stages using an advanced 3D plasmonic bimetallic alloy nanoarchitecture-based SERS biosensor combined with machine learning for multiple analyte identification. Adv Sci (Weinh), 2025, 12(14): e2414688.
72.	Pei Y, Chen L, Zhao Y, et al. Advances of immunosensors based on noble metal composite materials for detecting procalcitonin. Mikrochim Acta, 2025, 192(2): 72.
73.	Duolihong B, Ma X, Liu R, et al. Dual-signaling and ultrasensitive detection for PCT based on the photoelectric and electrocatalytic hydrogen evolution signals of Pt/Mo-CoFeS. Talanta, 2024, 273: 125945.
74.	Tseng YT, Yu YH, Yeh YY, et al. Femtomolar-level detection of procalcitonin using a split aptamer-based fiber optic nanogold-linked sorbent assay for diagnosis of sepsis. Talanta, 2025, 293: 128150.
75.	Barshilia D, Huang JJ, Komaram AC, et al. Ultrasensitive and rapid detection of procalcitonin via waveguide-enhanced nanogold-linked immunosorbent assay for early sepsis diagnosis. Nano Lett, 2024, 24(8): 2596-2602.
76.	Zhai GH, Zhang W, Xiang Z, et al. Diagnostic value of sIL-2R, TNF-α and PCT for sepsis infection in patients with closed abdominal injury complicated with severe multiple abdominal injuries. Front Immunol, 2021, 12: 741268.
77.	Zaki HA, Bensliman S, Bashir K, et al. Accuracy of procalcitonin for diagnosing sepsis in adult patients admitted to the emergency department: a systematic review and meta-analysis. Syst Rev, 2024, 13(1): 37.

1. Yuki K, Koutsogiannaki S. Pattern recognition receptors as therapeutic targets for bacterial, viral and fungal sepsis. Int Immunopharmacol, 2021, 98: 107909.
2. Ren ZY, Wang XR, Jia BQ, et al. Nanozyme-energized SERS sensor for ultrasensitive dual-mode bacterial detection. Acs Applied Nano Materials, 2025, 8(16): 8385-8396.
3. Xu JQ, Zhang WY, Fu JJ, et al. Viral sepsis: diagnosis, clinical features, pathogenesis, and clinical considerations. Mil Med Res, 2024, 11(1): 78.
4. Zhou Y, Zhang W, Cheng S, et al. Flexible PDMS-SERS platform for culture-free diagnosis of bacterial infections in clinical wound care. Talanta, 2025, 293: 128089.
5. Wu MY, Chen L, Chen Q, et al. Engineered phage with aggregation-induced emission photosensitizer in cocktail therapy against sepsis. Adv Mater, 2023, 35(6): e2208578.
6. Cross D, Drury R, Hill J, et al. Epigenetics in sepsis: understanding its role in endothelial dysfunction, immunosuppression, and potential therapeutics. Front Immunol, 2019, 10: 1363.
7. Scicluna BP, van Vught LA, Zwinderman AH, et al. Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study. Lancet Respir Med, 2017, 5(10): 816-826.
8. Saxena J, Das S, Kumar A, et al. Biomarkers in sepsis. Clin Chim Acta, 2024, 562: 119891.
9. Yao RQ, Ren C, Zheng LY, et al. Advances in immune monitoring approaches for sepsis-induced immunosuppression. Front Immunol, 2022, 13: 891024.
10. Barichello T, Generoso JS, Singer M, et al. Biomarkers for sepsis: more than just fever and leukocytosis-a narrative review. Crit Care, 2022, 26(1): 14.
11. He RR, Yue GL, Dong ML, et al. Sepsis biomarkers: advancements and clinical applications: a narrative review. Int J Mol Sci, 2024, 25(16): 9010.
12. Li F, Wang S, Gao Z, et al. Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring. Front Med (Lausanne), 2025, 11: 1510792.
13. Torres LK, Pickkers P, van der Poll T. Sepsis-induced immunosuppression. Annu Rev Physiol, 2022, 84: 157-181.
14. Liu D, Huang SY, Sun JH, et al. Sepsis-induced immunosuppression: mechanisms, diagnosis and current treatment options. Mil Med Res, 2022, 9(1): 56.
15. Yang J, Li H. The impact of aging and COVID-19 on our immune system: a high-resolution map from single cell analysis. Protein Cell, 2020, 11(10): 703-706.
16. Netea MG, Schlitzer A, Placek K, et al. Innate and adaptive immune memory: an evolutionary continuum in the host’s response to pathogens. Cell Host Microbe, 2019, 25(1): 13-26.
17. Zindel J, Kubes P. DAMPs, PAMPs, and LAMPs in immunity and sterile inflammation. Annu Rev Pathol, 2020, 15: 493-518.
18. Li D, Wu M. Pattern recognition receptors in health and diseases. Signal Transduct Target Ther, 2021, 6(1): 291.
19. Broz P, Monack DM. Newly described pattern recognition receptors team up against intracellular pathogens. Nat Rev Immunol, 2013, 13(8): 551-565.
20. Kufer TA, Creagh EM, Bryant CE. Guardians of the cell: effector-triggered immunity steers mammalian immune defense. Trends Immunol, 2019, 40(10): 939-951.
21. Gong T, Liu L, Jiang W, et al. DAMP-sensing receptors in sterile inflammation and inflammatory diseases. Nat Rev Immunol, 2020, 20(2): 95-112.
22. Wang X, Xia Z, Wang H, et al. Cell-membrane-coated nanoparticles for the fight against pathogenic bacteria, toxins, and inflammatory cytokines associated with sepsis. Theranostics, 2023, 13(10): 3224-3244.
23. Li Y, Zhang H, Chen C, et al. Biomimetic immunosuppressive exosomes that inhibit cytokine storms contribute to the alleviation of sepsis. Adv Mater, 2022, 34(19): e2108476.
24. Li Y, Yu J, Zeng Z, et al. Regulation of ubiquitination in sepsis: from PAMP versus DAMP to peripheral inflammation and cell death. Front Immunol, 2024, 15: 1513206.
25. Jiang Y, Gao S, Chen Z, et al. Pyroptosis in septic lung injury: interactions with other types of cell death. Biomed Pharmacother, 2023, 169: 115914.
26. Lazzaro A, De Girolamo G, Filippi V, et al. The interplay between host defense, infection, and clinical status in septic patients: a narrative review. Int J Mol Sci, 2022, 23(2): 803.
27. Azoulay E, Zuber J, Bousfiha AA, et al. Complement system activation: bridging physiology, pathophysiology, and therapy. Intensive Care Med, 2024, 50(11): 1791-1803.
28. de Nooijer AH, Kotsaki A, Kranidioti E, et al. Complement activation in severely ill patients with sepsis: no relationship with inflammation and disease severity. Crit Care, 2023, 27(1): 63.
29. Reis ES, Mastellos DC, Hajishengallis G, et al. New insights into the immune functions of complement. Nat Rev Immunol, 2019, 19(8): 503-516.
30. Chen S, Wu A, Shen X, et al. Disrupting the dangerous alliance: dual anti-inflammatory and anticoagulant strategy targets platelet-neutrophil crosstalk in sepsis. J Control Release, 2025, 379: 814-831.
31. Scully M, Levi M. How we manage haemostasis during sepsis. Br J Haematol, 2019, 185(2): 209-218.
32. Hernández-Jiménez E, Plata-Menchaca EP, Berbel D, et al. Assessing sepsis-induced immunosuppression to predict positive blood cultures. Front Immunol, 2024, 15: 1447523.
33. Cao C, Yu M, Chai Y. Pathological alteration and therapeutic implications of sepsis-induced immune cell apoptosis. Cell Death Dis, 2019, 10(10): 782.
34. Zheng LY, Duan Y, He PY, et al. Dysregulated dendritic cells in sepsis: functional impairment and regulated cell death. Cell Mol Biol Lett, 2024, 29(1): 81.
35. Gao X, Cai S, Li X, et al. Sepsis-induced immunosuppression: mechanisms, biomarkers and immunotherapy. Front Immunol, 2025, 16: 1577105.
36. Islam MM, Watanabe E, Salma U, et al. Immunoadjuvant therapy in the regulation of cell death in sepsis: recent advances and future directions. Front Immunol, 2024, 15: 1493214.
37. Molinaro R, Pastò A, Corbo C, et al. Macrophage-derived nanovesicles exert intrinsic anti-inflammatory properties and prolong survival in sepsis through a direct interaction with macrophages. Nanoscale, 2019, 11(28): 13576-13586.
38. Sehgal R, Maiwall R, Rajan V, et al. Granulocyte-macrophage colony-stimulating factor modulates myeloid-derived suppressor cells and treg activity in decompensated cirrhotic patients with sepsis. Front Immunol, 2022, 13: 828949.
39. Joshi I, Carney WP, Rock EP. Utility of monocyte HLA-DR and rationale for therapeutic GM-CSF in sepsis immunoparalysis. Front Immunol, 2023, 14: 1130214.
40. Lei S, Chen S, Zhong Q. Digital PCR for accurate quantification of pathogens: principles, applications, challenges and future prospects. Int J Biol Macromol, 2021, 184: 750-759.
41. Hou Y, Chen S, Zheng Y, et al. Droplet-based digital PCR (ddPCR) and its applications. Trac-Trends Anal. Chem, 2023, 158: 116897.
42. Wouters Y, Dalloyaux D, Christenhusz A, et al. Droplet digital polymerase chain reaction for rapid broad-spectrum detection of bloodstream infections. Microb Biotechnol, 2020, 13(3): 657-668.
43. Wu J, Tang B, Qiu Y, et al. Clinical validation of a multiplex droplet digital PCR for diagnosing suspected bloodstream infections in ICU practice: a promising diagnostic tool. Crit Care, 2022, 26(1): 243.
44. Park J, Lee KG, Han DH, et al. Pushbutton-activated microfluidic dropenser for droplet digital PCR. Biosens Bioelectron, 2021, 181: 113159.
45. Pan F, Altenried S, Scheibler S, et al. Ultrafast determination of antimicrobial resistant Staphylococcus aureus specifically captured by functionalized magnetic nanoclusters. ACS Sens, 2022, 7(11): 3491-3500.
46. Shrivastava S, Arya R, Kim KK, et al. A quorum-based fluorescent probe for imaging pathogenic bacteria. J Mater Chem B, 2022, 10(23): 4491-4500.
47. Zhao J, Li Y, Chen X, et al. Sensitive NIR fluorescence identification of bacteria in whole blood with bioorthogonal nanoprobes for early sepsis diagnosis. Anal Chem, 2023, 95(2): 955-965.
48. Liu X, Chen X, Yin S, et al. Dual-modal detection of antimicrobial susceptibility in pathogenic bacteria based on the high-throughput microfluidic platform. Chem Eng J, 2024, 499: 156506.
49. Zhou WM, Yan YY, Guo QR, et al. Microfluidics applications for high-throughput single cell sequencing. J Nanobiotechnology, 2021, 19(1): 312.
50. Saviano A, Henderson NC, Baumert TF. Single-cell genomics and spatial transcriptomics: discovery of novel cell states and cellular interactions in liver physiology and disease biology. J Hepatol, 2020, 73(5): 1219-1230.
51. Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol, 2018, 18(1): 35-45.
52. Yao RQ, Li ZX, Wang LX, et al. Single-cell transcriptome profiling of the immune space-time landscape reveals dendritic cell regulatory program in polymicrobial sepsis. Theranostics, 2022, 12(10): 4606-4628.
53. Liu Y, Li W, Lei L, et al. Effects of PGK1 on immunoinfiltration by integrated single-cell and bulk RNA-sequencing analysis in sepsis. Front Immunol, 2024, 15: 1449975.
54. Balch JA, Chen UI, Liesenfeld O, et al. Defining critical illness using immunological endotypes in patients with and without sepsis: a cohort study. Crit Care, 2023, 27(1): 292.
55. Komorowski M, Green A, Tatham KC, et al. Sepsis biomarkers and diagnostic tools with a focus on machine learning. EBioMedicine, 2022, 86: 104394.
56. Fu X, Ma W, Zuo Q, et al. Application of machine learning for high-throughput tumor marker screening. Life Sci, 2024, 348: 122634.
57. Zhang WY, Chen ZH, An XX, et al. Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning. World J Pediatr, 2023, 19(11): 1094-1103.
58. Baghela A, Pena OM, Lee AH, et al. Predicting sepsis severity at first clinical presentation: the role of endotypes and mechanistic signatures. EBioMedicine, 2022, 75: 103776.
59. Rajkomar A, Oren E, Chen K, et al. Scalable and accurate deep learning with electronic health records. NPJ Digit Med, 2018, 1: 18.
60. Prithula J, Islam KR, Kumar J, et al. A novel classical machine learning framework for early sepsis prediction using electronic health record data from ICU patients. Comput Biol Med, 2025, 184: 109284.
61. Barrios EL, Mazer MB, McGonagill PW, et al. Adverse outcomes and an immunosuppressed endotype in septic patients with reduced IFN-γ ELISpot. JCI Insight, 2024, 9(2): e175785.
62. Price AD, Becker ER, Barrios EL, et al. Surviving septic patients endotyped with a functional assay demonstrate active immune responses. Front Immunol, 2024, 15: 1418613.
63. Barrios EL, Balzano-Nogueira L, Polcz VE, et al. Unique lymphocyte transcriptomic profiles in septic patients with chronic critical illness. Front Immunol, 2024, 15: 1478471.
64. Bonavia AS, Samuelsen A, Chroneos ZC, et al. Comparison of rapid cytokine immunoassays for functional immune phenotyping. Front Immunol, 2022, 13: 940030.
65. Liu S, Lu F, Chen S, et al. Graphene oxide-based fluorescent biosensors for pathogenic bacteria detection: a review. Anal Chim Acta, 2025, 1337: 343428.
66. Ghorbani F, Abbaszadeh H, Mehdizadeh A, et al. Biosensors and nanobiosensors for rapid detection of autoimmune diseases: a review. Mikrochim Acta, 2019, 186(12): 838.
67. Wang Y, Guan M, Mi F, et al. Combining multisite functionalized magnetic nanomaterials with interference-free SERS nanotags for multi-target sepsis biomarker detection. Anal Chim Acta, 2023, 1272: 341523.
68. Guo R, Wang J, Zhao W, et al. A novel strategy for specific sensing and inactivation of Escherichia coli: constructing a targeted sandwich-type biosensor with multiple SERS hotspots to enhance SERS detection sensitivity and near-infrared light-triggered photothermal sterilization performance. Talanta, 2024, 269: 125466.
69. Wang C, Xu G, Wang W, et al. Bioinspired hot-spot engineering strategy towards ultrasensitive SERS sandwich biosensor for bacterial detection. Biosens Bioelectron, 2023, 237: 115497.
70. Lu TC, Yang YJ, Zhong Y, et al. Simultaneous detection of C-reactive protein and lipopolysaccharide based on a dual-channel electrochemical biosensor for rapid Gram-typing of bacterial sepsis. Biosens Bioelectron, 2024, 243: 115772.
71. Kim WH, Lee S, Jeon MJ, et al. Rapid and differential diagnosis of sepsis stages using an advanced 3D plasmonic bimetallic alloy nanoarchitecture-based SERS biosensor combined with machine learning for multiple analyte identification. Adv Sci (Weinh), 2025, 12(14): e2414688.
72. Pei Y, Chen L, Zhao Y, et al. Advances of immunosensors based on noble metal composite materials for detecting procalcitonin. Mikrochim Acta, 2025, 192(2): 72.
73. Duolihong B, Ma X, Liu R, et al. Dual-signaling and ultrasensitive detection for PCT based on the photoelectric and electrocatalytic hydrogen evolution signals of Pt/Mo-CoFeS. Talanta, 2024, 273: 125945.
74. Tseng YT, Yu YH, Yeh YY, et al. Femtomolar-level detection of procalcitonin using a split aptamer-based fiber optic nanogold-linked sorbent assay for diagnosis of sepsis. Talanta, 2025, 293: 128150.
75. Barshilia D, Huang JJ, Komaram AC, et al. Ultrasensitive and rapid detection of procalcitonin via waveguide-enhanced nanogold-linked immunosorbent assay for early sepsis diagnosis. Nano Lett, 2024, 24(8): 2596-2602.
76. Zhai GH, Zhang W, Xiang Z, et al. Diagnostic value of sIL-2R, TNF-α and PCT for sepsis infection in patients with closed abdominal injury complicated with severe multiple abdominal injuries. Front Immunol, 2021, 12: 741268.
77. Zaki HA, Bensliman S, Bashir K, et al. Accuracy of procalcitonin for diagnosing sepsis in adult patients admitted to the emergency department: a systematic review and meta-analysis. Syst Rev, 2024, 13(1): 37.

Previous Article
Research progress on ubiquitination modification in sepsis
Next Article
Research progress on the relationship between vitamin D and its receptor gene polymorphism and pain

West China Medical Journal

Sepsis diagnosis and treatment: recent advances in the detection of pathogen and host immune status

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content