Point-of-care diagnostics for sepsis using clinical biomarkers and microfluidic technology

A novel prognosis evaluation indicator of patients with sepsis created by integrating six microfluidic-based neutrophil chemotactic migration parameters

Impaired neutrophil migration in sepsis is associated with a poor prognosis. The potential of utilizing neutrophil chemotaxis to assess immune function, disease severity, and patient prognosis in sepsis remains underexplored. This study employed an innovative approach by integrating a multi-tip pipette with a Six-Unit microfluidic chip (SU6-chip) to establish gradients in six microchannels, thereby analyzing neutrophil chemotaxis in sepsis patients. We compared chemotactic parameters between healthy controls (NH = 20) and sepsis patients (NS1 = 25), observing significant differences in gradient perception time (GP), migration distance (MD), peak velocity (Vmax), chemotactic index (CI), reverse migration rate (RM), and stop migration number (SM). A novel composite indicator, the Sepsis Neutrophil Migration Evaluation (SNME) index, was developed by integrating these six chemotactic migration parameters. The SNME index and individual chemotaxis parameters showed significant correlations with the Sequential Organ Failure Assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation (APACHE II) score, hypersensitivity C-reactive protein (hs-CRP), and heparin-binding protein (HBP). Moreover, the SNME index demonstrated potential for monitoring sepsis progression, with ROC analysis confirming its predictive accuracy (area under the curve [AUC] = 0.895, cutoff value = 31.5, specificity = 86.73 %, sensitivity = 86.71 %), outperforming individual neutrophil chemotactic parameters. In conclusion, the SNME index represents a promising new tool for adjunctive diagnosis and prognosis assessment in patients with sepsis.

Combating Prozone Effects and Predicting the Dynamic Range of Naked-Eye Nanoplasmonic Biosensors through Capture Bioentity Optimization

Accurately quantifying high analyte concentrations poses a challenge due to the common occurrence of the prozone or hook effect within sandwich assays utilized in plasmonic nanoparticle-based lateral flow devices (LFDs). As a result, LFDs are often underestimated compared to other biosensors with concerns surrounding their specificity and sensitivity toward the target analyte. To address this limitation, here we develop an analytical model capable of predicting the prozone effect and subsequently the dynamic range of the biosensor based on the concentration of the capture antibody. To support our model, we conduct a sandwich immunoassay to detect C-reactive protein (CRP) in a phosphate-buffered saline (PBS) buffer using an LFD. Within the experiment, we investigate the relationship between the CRP dynamic range and the prozone effect as a function of the capture antibody concentration, which is increased from 0.1 to 2 mg/mL. The experimental results, while supporting the developed analytical model, show that increasing the capture antibody concentration increases the dynamic range. The developed model therefore holds the potential to expand the measurable range and reduce costs associated with quantifying biomarkers in diverse diagnostic assays. This will ultimately allow LFDs to have better clinical significance before the prozone effect becomes dominant.

Structure-Switching Electrochemical Aptasensor for Rapid, Reagentless, and Single-Step Nanomolar Detection of C-Reactive Protein

C-reactive protein (CRP) is an acute-phase reactant and sensitive indicator for sepsis and other life-threatening pathologies, including systemic inflammatory response syndrome. Currently, clinical turn-around times for established CRP detection methods take between 30 min to hours or even days from centralized laboratories. Here, we report the development of an electrochemical biosensor using redox probe-tagged DNA aptamers, functionalized onto inexpensive, commercially available screen-printed electrodes. Binding-induced conformational switching of the CRP-targeting aptamer induces a specific and selective signal-ON event, which enables single-step and reagentless detection of CRP in as little as 1 min. The aptasensor limit of detection spans approximately 20-60 nM in 50% human serum with dynamic response windows spanning 1-200 or 1-500 nM (R = 0.97/R = 0.98 respectively). The sensor is stable for at least 1 week and can be reused numerous times, as judged from repeated real-time dosing and dose-response assays. By decoupling binding events from the signal induction mechanism, structure-switching electrochemical aptamer-based sensors provide considerable advantages over their adsorption-based counterparts. Our work expands on the retinue of such sensors reported in the literature and is the first instance of structure-switching electrochemical aptamer-based sensors (SS-EABs) for reagentless, voltammetric CRP detection. We hope this study inspires further investigations into the suitability of SS-EABs for diagnostics, which will aid translational R&D toward fully realized devices aimed at point-of-care applications or for broader use by the public.

The Biomedical Applications of Biomolecule Integrated Biosensors for Cell Monitoring

Cell monitoring is essential for understanding the physiological conditions and cell abnormalities induced by various stimuli, such as stress factors, microbial invasion, and diseases. Currently, various techniques for detecting cell abnormalities and metabolites originating from specific cells are employed to obtain information on cells in terms of human health. Although the states of cells have traditionally been accessed using instrument-based analysis, this has been replaced by various sensor systems equipped with new materials and technologies. Various sensor systems have been developed for monitoring cells by recognizing biological markers such as proteins on cell surfaces, components on plasma membranes, secreted metabolites, and DNA sequences. Sensor systems are classified into subclasses, such as chemical sensors and biosensors, based on the components used to recognize the targets. In this review, we aim to outline the fundamental principles of sensor systems used for monitoring cells, encompassing both biosensors and chemical sensors. Specifically, we focus on biosensing systems in terms of the types of sensing and signal-transducing elements and introduce recent advancements and applications of biosensors. Finally, we address the present challenges in biosensor systems and the prospects that should be considered to enhance biosensor performance. Although this review covers the application of biosensors for monitoring cells, we believe that it can provide valuable insights for researchers and general readers interested in the advancements of biosensing and its further applications in biomedical fields.

A review of SERS coupled microfluidic platforms: From configurations to applications

Microfluidic systems have attracted considerable attention due to their low reagent consumption, short analysis time, and ease of integration in comparison to conventional methods, but still suffer from shortcomings in sensitivity and selectivity. Surface enhanced Raman scattering (SERS) offers several advantages in the detection of compounds, including label-free detection at the single-molecule level, and the narrow Raman peak width for multiplexing. Combining microfluidics with SERS is a viable way to improve their detection sensitivity. Researchers have recently developed several SERS coupled microfluidic platforms with substantial potential for biomolecular detection, cellular and bacterial analysis, and hazardous substance detection. We review the current development of SERS coupled microfluidic platforms, illustrate their detection principles and construction, and summarize the latest applications in biology, environmental protection and food safety. In addition, we innovatively summarize the current status of SERS coupled multi-mode microfluidic platforms with other detection technologies. Finally, we discuss the challenges and countermeasures during the development of SERS coupled microfluidic platforms, as well as predict the future development trend of SERS coupled microfluidic platforms.

Disposable Polyaniline/m-Phenylenediamine-Based Electrochemical Lactate Biosensor for Early Sepsis Diagnosis

Lactate serves as a crucial biomarker that indicates sepsis assessment in critically ill patients. A rapid, accurate, and portable analytical device for lactate detection is required. This work developed a stepwise polyurethane-polyaniline-m-phenylenediamine via a layer-by-layer based electrochemical biosensor, using a screen-printed gold electrode for lactate determination in blood samples. The developed lactate biosensor was electrochemically fabricated with layers of m-phenylenediamine, polyaniline, a crosslinking of a small amount of lactate oxidase via glutaraldehyde, and polyurethane as an outer membrane. The lactate determination using amperometry revealed the biosensor's performance with a wide linear range of 0.20-5.0 mmol L-1, a sensitivity of 12.17 ± 0.02 µA·mmol-1·L·cm-2, and a detection limit of 7.9 µmol L-1. The developed biosensor exhibited a fast response time of 5 s, high selectivity, excellent long-term storage stability over 10 weeks, and good reproducibility with 3.74% RSD. Additionally, the determination of lactate in human blood plasma using the developed lactate biosensor was examined. The results were in agreement with the enzymatic colorimetric gold standard method (p > 0.05). Our developed biosensor provides efficiency, reliability, and is a great potential tool for advancing lactate point-of-care testing applications in the early diagnosis of sepsis.

Diagnostic Accuracy of Point-of-Care Testing of C-Reactive Protein, Interleukin-6, and Procalcitonin in Neonates with Clinically Suspected Sepsis: A Prospective Observational Study

OBJECTIVE

Sepsis often prompts clinicians to start empirical antibiotics in suspected neonates while awaiting diagnosis. The next-generation testing with point-of-care (POC) techniques offers a lead-time advantage that could bridge the gap by providing a timely diagnosis.

MATERIALS AND METHODS

We conducted a prospective diagnostic study in 82 neonates enrolled between May and October 2022 in a level III neonatal intensive care unit. All neonates with a new episode of clinically suspected sepsis were included. Diagnostic accuracy of POC testing of C-reactive protein (CRP), interleukin-6 (IL-6), and procalcitonin (PCT) with standard laboratory methods was performed.

RESULTS

The mean gestation age and birth weight of the neonates were 33.17 ± 4.25 weeks and 1,695.4 ± 700.74 grams, respectively. Most neonates were preterm (75%) with nearly equal proportions of early (51.22%) and late-onset (48.78%) sepsis. The POC CRP correlated well with standard CRP (r = 0.8001, 95% CI: 0.706-0.867, p < 0.0001). Among the three biomarkers, CRP had the maximum diagnostic accuracy (area under the curve [AUC] - 0.73) followed by PCT (AUC - 0.65) and IL-6 (0.55). There was no significant difference in the diagnostic accuracy of CRP (p = 0.46), PCT (p = 0.29), and IL-6 (p = 0.60) in early- and late-onset sepsis. The mean time for POC estimation of IL-6, PCT, and CRP was 12 ± 3 min which was significantly less compared to 366 ± 61 min for standard techniques (p < 0.001).

CONCLUSION

POC CRP correlates well with standard techniques of estimation, and CRP alone and in combination with PCT has good diagnostic accuracy in neonatal sepsis.

Three-dimensional label-free morphology of CD8 + T cells as a sepsis biomarker

Sepsis is a dysregulated immune response to infection that leads to organ dysfunction and is associated with a high incidence and mortality rate. The lack of reliable biomarkers for diagnosing and prognosis of sepsis is a major challenge in its management. We aimed to investigate the potential of three-dimensional label-free CD8 + T cell morphology as a biomarker for sepsis. This study included three-time points in the sepsis recovery cohort (N = 8) and healthy controls (N = 20). Morphological features and spatial distribution within cells were compared among the patients' statuses. We developed a deep learning model to predict the diagnosis and prognosis of sepsis using the internal cell morphology. Correlation between the morphological features and clinical indices were analysed. Cell morphological features and spatial distribution differed significantly between patients with sepsis and healthy controls and between the survival and non-survival groups. The model for predicting the diagnosis and prognosis of sepsis showed an area under the receiver operating characteristic curve of nearly 100% with only a few cells, and a strong correlation between the morphological features and clinical indices was observed. Our study highlights the potential of three-dimensional label-free CD8 + T cell morphology as a promising biomarker for sepsis. This approach is rapid, requires a minimum amount of blood samples, and has the potential to provide valuable information for the early diagnosis and prognosis of sepsis.