Recent advances in developing biosensing based platforms for neonatal sepsis

Dual-Fluorescent Quantum Dot Nanobead-Based Lateral Flow Immunoassay for Simultaneous Detection of C-Reactive Protein and Procalcitonin

Simultaneous detection of C-reactive protein (CRP) and procalcitonin (PCT) at the point of care is crucial for the management of infections in patients with inflammation and in critical care settings. The challenge of detecting high concentrations of CRP alongside low concentrations of PCT in plasma from inflammatory patients has limited the clinical application of multiplexed immunoassays. Herein, we developed a lateral flow immunoassay (LFIA) that employs quantum dot nanobeads (QDNBs) of varying sizes and colors to enable the simultaneous quantification of PCT and CRP in human plasma. To extend the dynamic range of CRP detection, we combined QDNBs with smaller particle sizes with the CRP detection antibodies, thereby increasing the assay's dynamic range and reducing the hook effect. At the same time, the stronger fluorescence emitted by these larger QDNBs, in conjugation with the PCT detection antibodies, allows for the detection of PCT at the nanogram level, meeting the demand for high sensitivity. The results show that this method can detect CRP concentrations from 0.1 to 3 mg/L and PCT with a detection limit of 0.09 ng/mL, which is on par with clinically used methods. By employing this dual-color and dual-size QDNB labeling strategy, we successfully achieved simultaneous detection of CRP with a broad dynamic range and PCT with high sensitivity in a one-step point-of-care rapid test.

A self-driven microfluidic immunosensor for rapid separation, enrichment, and detection of biomarkers in serum

Biomarkers and their concentration levels are critical indicators of metabolomics for clinical applications. Rapid and sensitive analysis methods are essential for realizing timely and efficient quantitation of those significant biomarkers. In this work, a self-driven microfluidic immunosensor was developed for rapid all-in-one separation, enrichment, and detection of biomarkers. This immunosensor was constructed from a cyclic olefin copolymer (COC) channel layer and a polydimethylsiloxane (PDMS) sensing layer. The COC channel layer was modified through protein adsorption, immobilization, and remaining active site blocking. The obtained hydrophilic microchannels not only reduce the nonspecific adsorption, but also provide stable capillary-driven flow generation with linear velocities up to 20 mm/s for aqueous solution auto-injection. The PDMS sensing layer was modified using capture antibodies to accomplish affinity recognition of target biomarkers. Procalcitonin (PCT) and serum amyloid A (SAA) were selected as model biomarkers in the feasibility study on applying the self-driven microfluidic immunosensor to bioassay. The limits of detection of PCT and SAA were 7.9 ng/L and 7.6 μg/L, respectively. Moreover, the whole process can be accomplished within 60 min with excellent selectivity and reproducibility. In clinical serum sample analysis, satisfactory recoveries were achieved for PCT and SAA in the ranges of 85.0-103.0% and 95.5-106.0%, respectively, with relative standard deviations less than 5.3%. The method accuracy was further confirmed by the results of commercial immunoassay kits. This simple and easily operated immunosensor provides a rapid and sensitive biomarker analysis tool, and promotes the further development of automated and easy-to-use microfluidic immunoassays.

Diagnostic value of maternal, cord blood and neonatal biomarkers for early-onset sepsis: a systematic review and meta-analysis

BACKGROUND

An accurate diagnosis of early-onset sepsis (EOS) is challenging because of subtle symptoms and the lack of a good diagnostic tool, resulting in considerable antibiotic overtreatment. A biomarker, discriminating between infected and non-infected newborns at an early stage of the disease, could improve EOS prediction. Numerous biomarkers have been tested, but have never been compared directly.

OBJECTIVES

We aimed to provide a comprehensive overview of early biomarkers and their diagnostic value in maternal samples, umbilical cord blood, and neonatal serum.

DATA SOURCES

PubMed-Medline, EMBASE, The Cochrane Library, and Web of Science were searched up to 1 March 2023, without restrictions on publication date, population, or language.

STUDY ELIGIBILITY CRITERIA

Articles describing the diagnostic value of at least one biomarker in the detection of EOS in neonates, independent of gestational age, were included.

ASSESSMENT OF RISK OF BIAS

The QUADAS-2 tool was used to assess study quality.

METHODS OF DATA SYNTHESIS

Three independent researchers assessed the articles using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Meta-analysis was performed with all manuscripts describing diagnostic accuracy using a random-effects model.

RESULTS

Of 2296 identified articles, 171 reports were included in the systematic review and 69 in the meta-analysis. Literature showed mixed and inconsistent evidence for most biomarkers and sample types, because of a lack of a uniform EOS case definition, small sample sizes, and large heterogeneity between studies. Interesting markers were procalcitonin (pooled sensitivity 79%, 95% CI 71-84%; specificity 91%, 95% CI 83-96%, n = 11) and interleukin (IL)-6 (pooled sensitivity 83%, 95% CI 71-90%; specificity 87%, 95% CI 78-93%, n = 8) in umbilical cord blood and presepsin (pooled sensitivity 82%, 95% CI 62-93%; specificity 86%, 95% CI 73-93%, n = 3) and serum amyloid A (pooled sensitivity 92%, 95% CI 75-98%; specificity 96%, 95% CI 78-99%, n = 4) in neonatal serum. Studies on the combination of biomarkers were scarce.

CONCLUSIONS

A biomarker stand-alone test is currently not reliable for direct antibiotic stewardship in newborns, although several biomarkers show promising initial results. Further research into biomarker combinations could lead to an improved EOS diagnosis, reduce antibiotic overtreatment, and prevent associated health-related problems.

Challenges and Advances in Biomarker Detection for Rapid and Accurate Sepsis Diagnosis: An Electrochemical Approach

Sepsis is a life-threatening condition with high mortality rates due to delayed treatment of patients. The conventional methodology for blood diagnosis takes several hours, which suspends treatment, limits early drug administration, and affects the patient's recovery. Thus, rapid, accurate, bedside (onsite), economical, and reliable sepsis biomarker reading of the clinical sample is an emergent need for patient lifesaving. Electrochemical label-free biosensors are specific and rapid devices that are able to perform analysis at the patient's bedside; thus, they are considered an attractive methodology in a clinical setting. To reveal their full diagnostic potential, electrode architecture strategies of fabrication are highly desirable, particularly those able to preserve specific antibody-antigen attraction, restrict non-specific adsorption, and exhibit high sensitivity with a low detection limit for a target biomarker. The aim of this review is to provide state-of-the-art methodologies allowing the fabrication of ultrasensitive and highly selective electrochemical sensors for sepsis biomarkers. This review focuses on different methods of label-free biomarker sensors and discusses their advantages and disadvantages. Then, it highlights effective ways of avoiding false results and the role of molecular labels and functionalization. Recent literature on electrode materials and antibody grafting strategies is discussed, and the most efficient methodology for overcoming the non-specific attraction issues is listed. Finally, we discuss the existing electrode architecture for specific biomarker readers and promising tactics for achieving quick and low detection limits for sepsis biomarkers.

Nanomaterial-based methods for sepsis management

Sepsis is a serious disease caused by an impaired host immune response to infection, resulting in organ dysfunction, tissue damage and is responsible for high in-hospital mortality (approximately 20%). Recently, WHO documented sepsis as a global health priority. Nevertheless, there is still no effective and specific therapy for clinically detecting sepsis. Nanomaterial-based approaches have appeared as promising tools for identifying bacterial infections. In this review, recent biosensors are introduced and summarized as nanomaterial-based platforms for sepsis management and severe complications. Biosensors can be used as tools for the diagnosis and treatment of sepsis and as nanocarriers for drug delivery. In general, diagnostic methods for sepsis-associated bacteria, biosensors developed for this purpose are presented in detail, and their strengths and weaknesses are discussed. In other words, readers of this article will gain a comprehensive understanding of biosensors and their applications in sepsis management.

On-Site Fluorescent Detection of Sepsis-Inducing Bacteria using a Graphene-Oxide CRISPR-Cas12a (GO-CRISPR) System

Sepsis is an extremely dangerous medical condition that emanates from the body's response to a pre-existing infection. Early detection of sepsis-inducing bacterial infections can greatly enhance the treatment process and potentially prevent the onset of sepsis. However, current point-of-care (POC) sensors are often complex and costly or lack the ideal sensitivity for effective bacterial detection. Therefore, it is crucial to develop rapid and sensitive biosensors for the on-site detection of sepsis-inducing bacteria. Herein, we developed a graphene oxide CRISPR-Cas12a (GO-CRISPR) biosensor for the detection of sepsis-inducing bacteria in human serum. In this strategy, single-stranded (ssDNA) FAM probes were quenched with single-layer graphene oxide (GO). Target-activated Cas12a trans-cleavage was utilized for the degradation of the ssDNA probes, detaching the short ssDNA probes from GO and recovering the fluorescent signals. Under optimal conditions, we employed our GO-CRISPR system for the detection of Salmonella Typhimurium (S. Typhimurium) with a detection sensitivity of as low as 3 × 103 CFU/mL in human serum, as well as a good detection specificity toward other competing bacteria. In addition, the GO-CRISPR biosensor exhibited excellent sensitivity to the detection of S. Typhimurium in spiked human serum. The GO-CRISPR system offers superior rapidity for the detection of sepsis-inducing bacteria and has the potential to enhance the early detection of bacterial infections in resource-limited settings, expediting the response for patients at risk of sepsis.

Rational Design of Flexible Mechanical Force Sensors for Healthcare and Diagnosis

Over the past decade, there has been a significant surge in interest in flexible mechanical force sensing devices and systems. Tremendous efforts have been devoted to the development of flexible mechanical force sensors for daily healthcare and medical diagnosis, driven by the increasing demand for wearable/portable devices in long-term healthcare and precision medicine. In this review, we summarize recent advances in diverse categories of flexible mechanical force sensors, covering piezoresistive, capacitive, piezoelectric, triboelectric, magnetoelastic, and other force sensors. This review focuses on their working principles, design strategies and applications in healthcare and diagnosis, with an emphasis on the interplay among the sensor architecture, performance, and application scenario. Finally, we provide perspectives on the remaining challenges and opportunities in this field, with particular discussions on problem-driven force sensor designs, as well as developments of novel sensor architectures and intelligent mechanical force sensing systems.

Advancement in biomarker based effective diagnosis of neonatal sepsis

Neonatal sepsis is considered as alarming medical emergency and becomes the common global reason of neonatal mortality. Non-specific symptoms and limitations of conventional diagnostic methods for neonatal sepsis mandate fast and reliable method to diagnose disease for point of care application. Recently, disease specific biomarkers have gained interest for rapid diagnosis that led to the development of electrochemical biosensor with enhanced specificity, sensitivity, cost-effectiveness and user-friendliness. Other than conventional biomarker C-reactive protein to diagnose neonatal sepsis, several potential biomarkers including Procalcitonin (PCT), Serum amyloid A (SAA) and other candidates are extensively investigated. The present review provides insights on advancements and diagnostic abilities of protein and nucleotide based biomarkers with their incorporation in developing electrochemical biosensors by employing novel fabrication strategies. This review provides an overview of most promising biomarker and its capability for neonatal sepsis diagnosis to fulfil future demand to develop electrochemical biosensor for point-of-care applications.

Single-molecule lipopolysaccharides identification and the interplay with biomolecules via nanopore readout

Lipopolysaccharides (LPS) are the major constituent on the cell envelope of all gram-negative bacteria. They are ubiquitous in air, and are toxic inflammatory stimulators for urinary disorders and sepsis. The reported optical, thermal, and electrochemical sensors via the intermolecular interplay of LPS with proteins and aptamers are generally complicated methods. We demonstrate the single-molecule nanopore approach for LPS identification in distinct bacteria as well as the serotypes discrimination. With a 4 nm nanopore, we achieve a detection limit of 10 ng/mL. Both the antibiotic polymyxin B (PMB) and DNA aptamer display specific binding to LPS. The identification of LPS in both human serum and tap water show good performance with nanopore platforms. Our work shows a highly-sensitive and easy-to-handle scheme for clinical and environmental biomarkers determination and provides a promising screening tool for early warning of contamination in water and medical supplies.

Clinical Value of Laboratory Biomarkers for the Diagnosis and Early Identification of Culture-Positive Sepsis in Neonates

Background

Neonatal sepsis (NS) is an important cause of mortality and morbidity in newborn infants. However, early diagnosis of proven sepsis (culture-positive sepsis) is difficult. We aimed to define the best combination of biomarkers to diagnose the onset of neonatal sepsis, distinguish culture-positive neonatal sepsis and predict the time of confirmation of neonatal sepsis.

Methods

This retrospective cohort study was conducted from January 2016 to December 2020. Clinical characteristics and laboratory results were collected from the electronic medical records. Hematology profiles and biochemical indices were obtained upon hospital admission. Multivariate logistic regression analysis was used to evaluate the risk factors and construct a nomogram. The performance of the nomogram was evaluated by receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Multivariable linear regression was used to identify the association between admission-to-diagnosis interval (ADI) and correlated variables.

Results

Overall, 148 infants with neonatal sepsis (67 culture positive sepsis and 81 culture negative sepsis) and 150 controls were included. C-reactive protein (CRP) (p<0.001), platelets (PLT) (p=0.011), urea nitrogen (BUN) (p=0.001) and conjugated bilirubin (BC) (p=0.007) were independent risk factors for neonatal sepsis. The diagnostic nomogram based on CRP, PLT, BUN and BC showed excellent diagnostic accuracy for neonatal sepsis (AUC=0.928). The nomogram based on red blood cell distribution width (RDW) and mean platelet volume (MPV) was efficient in distinguishing proven neonatal sepsis from clinical sepsis, with an AUC of 0.700 in the training group and 0.689 in the validation group. Decision curve analysis (DCA) showed that the nomogram had good clinical utility. Multivariable analysis revealed gestational age, CRP, and MPV were significantly associated with admission-to-diagnosis interval in culture-positive sepsis (p < 0.001).

Conclusion

Different combinations biomarkers were performant to diagnose the onset of neonatal sepsis, distinguish culture-positive neonatal sepsis, predict the time of confirmation, and aid in individual therapy.

Nano-Biotechnology for Bacteria Identification and Potent Anti-bacterial Properties: A Review of Current State of the Art

Sepsis is a critical disease caused by the abrupt increase of bacteria in human blood, which subsequently causes a cytokine storm. Early identification of bacteria is critical to treating a patient with proper antibiotics to avoid sepsis. However, conventional culture-based identification takes a long time. Polymerase chain reaction (PCR) is not so successful because of the complexity and similarity in the genome sequence of some bacterial species, making it difficult to design primers and thus less suitable for rapid bacterial identification. To address these issues, several new technologies have been developed. Recent advances in nanotechnology have shown great potential for fast and accurate bacterial identification. The most promising strategy in nanotechnology involves the use of nanoparticles, which has led to the advancement of highly specific and sensitive biosensors capable of detecting and identifying bacteria even at low concentrations in very little time. The primary drawback of conventional antibiotics is the potential for antimicrobial resistance, which can lead to the development of superbacteria, making them difficult to treat. The incorporation of diverse nanomaterials and designs of nanomaterials has been utilized to kill bacteria efficiently. Nanomaterials with distinct physicochemical properties, such as optical and magnetic properties, including plasmonic and magnetic nanoparticles, have been extensively studied for their potential to efficiently kill bacteria. In this review, we are emphasizing the recent advances in nano-biotechnologies for bacterial identification and anti-bacterial properties. The basic principles of new technologies, as well as their future challenges, have been discussed.

Designing of a unique bioreceptor and fabrication of an efficient genosensing platform for neonatal sepsis detection

We report the results of studies related to the fabrication of a nanostructured graphene oxide (GO)-based electrochemical genosensor for neonatal sepsis detection. Initially, we selected the fimA gene of E. coli for nenonatal sepsis detection and further designed a 20-mer long amine-terminated oligonucleotide. This designed oligonucleotide will work as a bioreceptor for the detection of the virulent fimA gene. An electrochemical genosensor was further developed where GO was used as an immobilization matrix. For the formation of a thin film of GO on an indium tin oxide (ITO)-coated glass electrode, an optimized DC potential of 10 V for 90 s was applied via an electrophoretic deposition unit. Thereafter, the designed oligonucleotides were immobilized through EDC-NHS chemistry. The nanomaterial and fabricated electrodes were characterized via X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy and cyclic voltammetry techniques. The fabricated genosensor (BSA/pDNA/GO/ITO) has the ability to detect the target fimA gene with a linear detection range of 10-12 M to 10-6 M, a lower detection limit of 10-12 M and a sensitivity of 114.7 μA M-1 cm-2. We also investigated the biosensing ability of the developed genosensor in an artificial serum sample and the obtained electrochemical results were within the acceptable percentage relative standard deviation (% RSD), indicating that the fabricated genosensor can be used for the detection of neonatal sepsis by using a serum sample.

Group B Streptococcus Early-Onset Disease: New Preventive and Diagnostic Tools to Decrease the Burden of Antibiotic Use

The difficulty in recognizing early-onset neonatal sepsis (EONS) in a timely manner due to non-specific symptoms and the limitations of diagnostic tests, combined with the risk of serious consequences if EONS is not treated in a timely manner, has resulted in a low threshold for starting empirical antibiotic treatment. New guideline strategies, such as the neonatal sepsis calculator, have been proven to reduce the antibiotic burden related to EONS, but lack sensitivity for detecting EONS. In this review, the potential of novel, targeted preventive and diagnostic methods for EONS is discussed from three different perspectives: maternal, umbilical cord and newborn perspectives. Promising strategies from the maternal perspective include Group B Streptococcus (GBS) prevention, exploring the virulence factors of GBS, maternal immunization and antepartum biomarkers. The diagnostic methods obtained from the umbilical cord are preliminary but promising. Finally, promising fields from the newborn perspective include biomarkers, new microbiological techniques and clinical prediction and monitoring strategies. Consensus on the definition of EONS and the standardization of research on novel diagnostic biomarkers are crucial for future implementation and to reduce current antibiotic overexposure in newborns.

Electrochemical Biosensors as a Novel Platform in the Identification of Listeriosis Infection

Listeria monocytogenes (L.M.) is a gram-positive bacillus with wide distribution in the environment. This bacterium contaminates water sources and food products and can be transmitted to the human population. The infection caused by L.M. is called listeriosis and is common in pregnant women, immune-deficient patients, and older adults. Based on the released statistics, listeriosis has a high rate of hospitalization and mortality; thus, rapid and timely detection of food contamination and listeriosis cases is necessary. During the last few decades, biosensors have been used for the detection and monitoring of varied bacteria species. These devices are detection platforms with great sensitivity and low detection limits. Among different types of biosensors, electrochemical biosensors have a high capability to circumvent several drawbacks associated with the application of conventional laboratory techniques. In this review article, different electrochemical biosensor types used for the detection of listeriosis were discussed in terms of actuators, bioreceptors, specific working electrodes, and signal amplification. We hope that this review will facilitate researchers to access a complete and comprehensive template for pathogen detection based on the different formats of electrochemical biosensors.

High prevalence of Panton-Valentine Leucocidin (PVL) toxin carrying MRSA and multidrug resistant gram negative bacteria in late onset neonatal sepsis indicate nosocomial spread in a Pakistani tertiary care hospital

BACKGROUND

Neonatal sepsis has high incidence with significant mortality and morbidity rates in Pakistan. We investigated common etiological patterns of neonatal sepsis at a tertiary care setup.

METHODS

90 pus and blood, gram negative and gram positive bacterial isolates were analyzed for virulence and antibiotic resistance gene profiling using PCR and disc diffusion methods.

RESULTS

Staphylococcus aureus showed strong association with neonatal sepsis (43 %) followed by Citrobacter freundii (21 %), Pseudomonas aeruginosa (13 %), Escherichia coli (15 %) and Salmonella enterica (8 %). Molecular typing of E. coli isolates depicted high prevalence of the virulent F and B2 phylogroups, with 4 hypervirulent phylogroup G isolates. 76.9 % S. aureus isolates showed presence of Luk-PV, encoding for Panton-valentine leucocidin (PVL) toxin with majority also carrying MecA gene and classified as methicillin resistant S. aureus (MRSA). ecpA, papC, fimH and traT virulence genes were detected in E. coli and Salmonella isolates. 47 % Citrobacter freundii isolates carried the shiga like toxin SltII B. Antimicrobial resistance profiling depicted common resistance to cephalosporins, beta lactams and fluoroquinolones.

CONCLUSION

Presence of PVL carrying MRSA and multidrug resistant gram negative bacteria, all isolated from late onset sepsis neonates indicate a predominant nosocomial transmission pattern which may complicate management of the disease in NICU setups.

The Endothelial Glycocalyx and Neonatal Sepsis

Sepsis carries a substantial risk of morbidity and mortality in newborns, especially preterm-born neonates. Endothelial glycocalyx (eGC) is a carbohydrate-rich layer lining the vascular endothelium, with important vascular barrier function and cell adhesion properties, serving also as a mechano-sensor for blood flow. eGC shedding is recognized as a fundamental pathophysiological process generating microvascular dysfunction, which in turn contributes to multiple organ failure and death in sepsis. Although the disruption of eGC and its consequences have been investigated intensively in the adult population, its composition, development, and potential mechanisms of action are still poorly studied during the neonatal period, and more specifically, in neonatal sepsis. Further knowledge on this topic may provide a better understanding of the molecular mechanisms that guide the sepsis pathology during the neonatal period, and would increase the usefulness of endothelial glycocalyx dysfunction as a diagnostic and prognostic biomarker. We reviewed several components of the eGC that help to deeply understand the mechanisms involved in the eGC disruption during the neonatal period. In addition, we evaluated the potential of eGC components as biomarkers and future targets to develop therapeutic strategies for neonatal sepsis.

An Entropy-Based Architecture for Detection of Sepsis in Newborn Cry Diagnostic Systems

The acoustic characteristics of cries are an exhibition of an infant's health condition and these characteristics have been acknowledged as indicators for various pathologies. This study focused on the detection of infants suffering from sepsis by developing a simplified design using acoustic features and conventional classifiers. The features for the proposed framework were Mel-frequency Cepstral Coefficients (MFCC), Spectral Entropy Cepstral Coefficients (SENCC) and Spectral Centroid Cepstral Coefficients (SCCC), which were classified through K-nearest Neighborhood (KNN) and Support Vector Machine (SVM) classification methods. The performance of the different combinations of the feature sets was also evaluated based on several measures such as accuracy, F1-score and Matthews Correlation Coefficient (MCC). Bayesian Hyperparameter Optimization (BHPO) was employed to tailor the classifiers uniquely to fit each experiment. The proposed methodology was tested on two datasets of expiratory cries (EXP) and voiced inspiratory cries (INSV). The highest accuracy and F-score were 89.99% and 89.70%, respectively. This framework also implemented a novel feature selection method based on Fuzzy Entropy (FE) as a final experiment. By employing FE, the number of features was reduced by more than 40%, whereas the evaluation measures were not hindered for the EXP dataset and were even enhanced for the INSV dataset. Therefore, it was deduced through these experiments that an entropy-based framework is successful for identifying sepsis in neonates and has the advantage of achieving high performance with conventional machine learning (ML) approaches, which makes it a reliable means for the early diagnosis of sepsis in deprived areas of the world.

Engineering single-atom catalysts toward biomedical applications

Due to inherent structural defects, common nanocatalysts always display limited catalytic activity and selectivity, making it practically difficult for them to replace natural enzymes in a broad scope of biologically important applications. By decreasing the size of the nanocatalysts, their catalytic activity and selectivity will be substantially improved. Guided by this concept, the advances of nanocatalysts now enter an era of atomic-level precise control. Single-atom catalysts (denoted as SACs), characterized by atomically dispersed active sites, strikingly show utmost atomic utilization, precisely located metal centers, unique metal-support interactions and identical coordination environments. Such advantages of SACs drastically boost the specific activity per metal atom, and thus provide great potential for achieving superior catalytic activity and selectivity to functionally mimic or even outperform natural enzymes of interest. Although the size of the catalysts does matter, it is not clear whether the guideline of "the smaller, the better" is still correct for developing catalysts at the single-atom scale. Thus, it is clearly a new, urgent issue to address before further extending SACs into biomedical applications, representing an important branch of nanomedicine. This review begins by providing an overview of recent advances of synthesis strategies of SACs, which serve as a basis for the discussion of emerging achievements in improving the enzyme-like catalytic properties at an atomic level. Then, we carefully compare the structures and functions of catalysts at various scales from nanoparticles, nanoclusters, and few-atom clusters to single atoms. Contrary to conventional wisdom, SACs are not the most catalytically active catalysts in specific reactions, especially those requiring multi-site auxiliary activities. After that, we highlight the unique roles of SACs toward biomedical applications. To appreciate these advances, the challenges and prospects in rapidly growing studies of SACs-related catalytic nanomedicine are also discussed in this review.

Biomarkers of Neonatal Sepsis: From Being Mere Numbers to Becoming Guiding Diagnostics

Neonatal sepsis is a common cause of neonatal morbidity and mortality. The diagnosis of newborn sepsis is still difficult. Different early objective diagnostic tests or specific signs and symptoms, particularly in preterm infants, make it difficult to diagnose neonatal sepsis. This review article describes biomarkers and their role in the early diagnosis, treatment, and prognosis of neonatal sepsis. It also explores the possible advances and future prospects of these biomarkers. An ideal sepsis biomarker will not only help in the guidance of the use of antibiotics when not needed but also the duration of the course of antibiotics if sepsis is proven. It should also have high sensitivity, specificity, positive predictive value, and negative predictive value. These biomarkers hold a promising position in the management of neonatal sepsis and translate into use in clinical settings. Metabolomics, a diagnostic method based on detecting metabolites found in biological fluids, may open new possibilities in the management of critically ill newborns.

Fabrication of a sensing platform for identification of tumor necrosis factor-alpha: a biomarker for neonatal sepsis

Neonatal sepsis is a prime cause of neonatal deaths across the globe. Presently, various medical tests and biodevices are available in neonatal care. These diagnosis platforms possess several limitations such as being highly expensive, time-consuming, or requiring skilled professionals for operation. These limitations can be overcome through biosensor development. This work discusses the assembling of an electrochemical sensing platform that is designed to detect the level of tumor necrosis factor-alpha (TNF-α). The sensing platform was moderated with nanomaterials molybdenum disulfide nanosheets (MoS₂NSs) and silicon dioxide-modified iron oxide nanoparticles (Fe₃O₄@SiO₂NPs). The integration of nanomaterials helps in accomplishing the improved characteristics of the biosensor in terms of conductivity, selectivity, and sensitivity. Further, the molecularly imprinted polymer (MIP) approach was incorporated for sensing the presence of TNF-α on the surface of the working electrode. The electrochemical response of the electrode was recorded at different conditions. A broad concentration range was selected to optimize the biosensor from 0.01 pM to 100 nM. The sensitivity of the biosensor was higher and it exhibits a lower detection limit (0.01 pM).

Prediction for late-onset sepsis in preterm infants based on data from East China

AIM

To construct a prediction model based on the data of premature infants and to apply the data in our study as external validation to the prediction model proposed by Yuejun Huang et al. to evaluate the predictive ability of both models.

METHODS

In total, 397 premature infants were randomly divided into the training set (n = 278) and the testing set (n = 119). Univariate and multivariate logistic analyses were applied to identify potential predictors, and the prediction model was constructed based on the predictors. The area under the curve (AUC) value, the receiver operator characteristic (ROC) curves, and the calibration curves were used to evaluate the predictive performances of prediction models. The data in our study were used in the prediction model proposed by Yuejun Huang et al. as external validation.

RESULTS

In the current study, endotracheal intubation [odds ratio (OR) = 10.553, 95% confidence interval (CI): 4.959-22.458], mechanical ventilation (OR = 10.243, 95% CI: 4.811-21.806), asphyxia (OR = 2.614, 95% CI: 1.536-4.447), and antibiotics use (OR = 3.362, 95% CI: 1.454-7.775) were risk factors for late-onset sepsis in preterm infants. The higher birth weight of infants (OR = 0.312, 95% CI: 0.165-0.588) and gestational age were protective factors for late-onset sepsis in preterm infants. The training set was applied for the construction of the models, and the testing set was used to test the diagnostic efficiency of the model. The AUC values of the prediction model were 0.760 in the training set and 0.796 in the testing set.

CONCLUSION

The prediction model showed a good predictive ability for late-onset sepsis in preterm infants.

Bio-Functionalized Magnetic Nanoparticles for the Immunoassay of C-Reactive Protein and Procalcitonin in Cervicovaginal Secretions of Pregnant Women with Preterm Prelabor Rupture of Membranes to Predict Early-Onset Neonatal Sepsis

Purpose

Early-onset sepsis is a major cause of neonatal morbidity and mortality. C-reactive protein (CRP) and procalcitonin (PCT) are acute phase reactants related to infection. The aim of this study was to explore the feasibility of measuring CRP and PCT concentrations in cervicovaginal secretions of pregnant women with preterm prelabor rupture of membranes (PPROM) using an immunomagnetic reduction (IMR) assay to predict early-onset neonatal sepsis.

Patients and Methods

This prospective study was performed at Mackay Memorial Hospital, Taipei, Taiwan from February 2015 to January 2018. Pregnant women with PPROM between 22 and 34 weeks of gestation were recruited. CRP and PCT concentrations in cervicovaginal secretions were measured using an IMR assay.

Results

Thirty-five cervicovaginal secretion samples were obtained. After excluding two neonatal deaths, early-onset neonatal sepsis was diagnosed in 15 of the 33 surviving neonates. There was no significant relationship between cervicovaginal secretion CRP level and neonatal sepsis; however, cervicovaginal secretion PCT levels were significantly higher in the neonatal sepsis group than in the non-sepsis group (45.99 vs 9.54 ng/mL, P = 0.039). Receiver operating characteristic (ROC) curve analysis revealed a PCT cut-off level of 20.60 ng/mL to predict early-onset sepsis, and the area under the ROC curve was 0.71 (95% confidence interval 0.52 to 0.90, P = 0.039), with sensitivity and specificity of 73.3% and 77.8%, respectively.

Conclusion

Measuring the concentration of PCT in cervicovaginal secretions with an IMR assay can predict early-onset sepsis in neonates born to mothers with PPROM.

The Potential of Drug Delivery Nanosystems for Sepsis Treatment

Sepsis is a major immune response disorder caused by infection, with very high incidence and mortality rates. In the clinic, sepsis and its complications are mainly controlled and treated with antibiotics, anti-inflammatory, and antioxidant drugs. However, these treatments have some shortcomings, such as rapid metabolism and severe side effects. The emergence of drug delivery nanosystems can significantly improve tissue permeability, prolong drugs' circulation time, and reduce side effects. In this paper, we reviewed recent drug delivery nanosystems designed for sepsis treatment based on their mechanisms (anti-bacterial, anti-inflammatory, and antioxidant). Although great progress has been made recently, clinical practice transformation is still very difficult. Therefore, we also discussed key obstacles, including tissue distribution, overcoming bacterial resistance, and single treatment modes. Finally, a rigorous optimization of drug delivery nanosystems is expected to present great potential for sepsis therapy.

Neonatal bloodstream infections

PURPOSE OF REVIEW

Neonatal bloodstream infections (BSI) are a major contributor to morbidity and mortality within neonatal intensive care units. BSI, including central line-associated BSI, have decreased over the past 15 years but remain common in extremely preterm infants. The purpose of this review is to highlight recent advances in the causes, diagnosis, management, and prevention of neonatal BSI.

RECENT FINDINGS

Continued quality improvement efforts and bundles have reduced BSI incidence, and novel approaches are highlighted. An update of emerging pathogens as well as traditional pathogens with novel antimicrobial resistance, which are an increasingly common cause of neonatal BSI, is included. Finally, current and future investigations into serum or noninvasive biomarkers for neonatal BSI are reviewed.

SUMMARY

Neonatal BSIs continue to decrease due to enhanced infection control and prevention techniques. However, many challenges remain, including emerging bacterial and fungal resistance and the continued need for novel diagnostics that hasten time to pathogen identification and effective treatment. This review of the past 18 months highlights the rapid changes in this area. Ongoing efforts to reduce the morbidity and mortality caused by neonatal BSI must remain a priority.

Chemically and Biologically Engineered Bacteria-Based Delivery Systems for Emerging Diagnosis and Advanced Therapy

Bacteria are one of the main groups of organisms, which dynamically and closely participate in human health and disease development. With the integration of chemical biotechnology, bacteria have been utilized as an emerging delivery system for various biomedical applications. Given the unique features of bacteria such as their intrinsic biocompatibility and motility, bacteria-based delivery systems have drawn wide interest in the diagnosis and treatment of various diseases, including cancer, infectious diseases, kidney failure, and hyperammonemia. Notably, at the interface of chemical biotechnology and bacteria, many research opportunities have been initiated, opening a promising frontier in biomedical application. Herein, the current synergy of chemical biotechnology and bacteria, the design principles for bacteria-based delivery systems, the microbial modulation, and the clinical translation are reviewed, with a special focus on the emerging advances in diagnosis and therapy.

Nanobody-based immunosensing methods for safeguarding public health

Immunosensing methods are biosensing techniques based on specific recognition of an antigen-antibody immunocomplex, which have become commonly used in safeguarding public health. Taking advantage of antibody-related biotechnological advances, the utilization of an antigen-binding fragment of a heavy-chain-only antibody termed as 'nanobody' holds significant biomedical potential. Compared with the conventional full-length antibody, a single-domain nanobody retaining cognate antigen specificity possesses remarkable physicochemical stability and structural adaptability, which enables a flexible and efficient molecular design of the immunosensing strategy. This minireview aims to summarize the recent progress in immunosensing methods using nanobody targeting tumor markers, environmental pollutants, and foodborne microbes.

Serum amyloid A - A prime candidate for identification of neonatal sepsis

Neonatal sepsis is common, lethal, and hard to diagnose. In combination with clinical findings and blood culture, biomarkers are crucial to make the correct diagnose. A Swedish national inquiry indicated that neonatologists were not quite satisfied with the available biomarkers. We assessed the kinetics of 15 biomarkers simultaneously: ferritin, fibrinogen, granulocyte colony-stimulating factor (G-CSF), interferon (IFN)-γ, interleukin (IL)-1β, -6, -8, -10, macrophage inflammatory protein (MIP)-1β, procalcitonin, resistin, serum amyloid A (SAA), tumor necrosis factor (TNF)-α, tissue plasminogen activator-3 and visfatin. The goal was to observe how quickly they rise in response to infection, and for how long they remain elevated. From a neonatal intensive care unit, newborns ≥28 weeks gestational age were recruited. Sixty-eight newborns were recruited to the study group (SG), and fifty-one to the control group (CG). The study group subjects were divided into three subgroups depending on clinical findings: confirmed sepsis (CSG), suspected sepsis (SSG) and no sepsis. CSG and SSG were also merged into an entire sepsis group (ESG) for sub-analysis. Blood samples were collected at three time-points; 0 h, 12-24 h and 48-72 h, in order to mimic a "clinical setting". At 0 h, visfatin was elevated in SSG compared to CG; G-CSF, IFN-γ, IL-1β, -8 and - 10 were elevated in SSG and ESG compared to CG, whereas IL-6 and SAA were elevated in all groups compared to CG. At 12-24 h, IL-8 was elevated in ESG compared to CG, visfatin was elevated in ESG and SSG compared to CG, and SAA was elevated in all three groups compared to CG. At 48-72 h, fibrinogen was elevated in ESG compared to CG, IFN-γ and IL-1β were elevated in SSG and ESG compared to CG, whereas IL-8 and SAA were elevated in all three groups compared to CG. A function of time-formula is introduced as a tool for theoretical prediction of biomarker levels at any time-point. We conclude that SAA has the most favorable kinetics regarding diagnosing neonatal sepsis, of the biomarkers studied. It is also readily available methodologically, making it a prime candidate for clinical use.

Biomarkers for the Diagnosis of Neonatal Sepsis

Neonatal sepsis is a major cause of morbidity and mortality in neonates and is challenging to diagnose. Infants manifest nonspecific clinical signs in response to sepsis; these signs may be caused by noninfectious conditions. Time to antibiotics affects neonatal sepsis outcome, so clinicians need to identify and treat neonates with sepsis expeditiously. Clinicians use serum biomarkers to measure inflammation and infection and assess the infant's risk of sepsis. However, current biomarkers lack sufficient sensitivity or specificity to be consider useful diagnostic tools. Continued research to identify novel biomarkers as well as novel ways of measuring them is sorely needed.