Direct detection of malaria infected red blood cells by surface enhanced Raman spectroscopy

Unveiling practical considerations for reliable and standardized SERS measurements: lessons from a comprehensive review of oblique angle deposition-fabricated silver nanorod array substrates

Recently, there has been an exponential growth in the number of publications focusing on surface-enhanced Raman scattering (SERS), primarily driven by advancements in nanotechnology and the increasing demand for chemical and biological detection. While many of these publications have focused on the development of new substrates and detection-based applications, there is a noticeable lack of attention given to various practical issues related to SERS measurements and detection. This review aims to fill this gap by utilizing silver nanorod (AgNR) SERS substrates fabricated through the oblique angle deposition method as an illustrative example. The review highlights and addresses a range of practical issues associated with SERS measurements and detection. These include the optimization of SERS substrates in terms of morphology and structural design, considerations for measurement configurations such as polarization and the incident angle of the excitation laser, and exploration of enhancement mechanisms encompassing both intrinsic properties induced by the structure and materials, as well as extrinsic factors arising from wetting/dewetting phenomena and analyte size. The manufacturing and storage aspects of SERS substrates, including scalable fabrication techniques, contamination control, cleaning procedures, and appropriate storage methods, are also discussed. Furthermore, the review delves into device design considerations, such as well arrays, flow cells, and fiber probes, and explores various sample preparation methods such as drop-cast and immersion. Measurement issues, including the effect of excitation laser wavelength and power, as well as the influence of buffer, are thoroughly examined. Additionally, the review discusses spectral analysis techniques, encompassing baseline removal, chemometric analysis, and machine learning approaches. The wide range of AgNR-based applications of SERS, across various fields, is also explored. Throughout the comprehensive review, key lessons learned from collective findings are outlined and analyzed, particularly in the context of detailed SERS measurements and standardization. The review also provides insights into future challenges and perspectives in the field of SERS. It is our hope that this comprehensive review will serve as a valuable reference for researchers seeking to embark on in-depth studies and applications involving their own SERS substrates.

A magnetic field augmented ultra-thin layer chromatography coupled surface enhanced Raman spectroscopy separation of hemozoin from bacterial mixture

Malaria is considered as one the most widespread disease with highest possibility of co-infection at all levels of the disease prognosis. Rapid detection and discrimination of malaria from other co-infections remains a challenge. Hemozoin is a metabolic biproduct of malaraia possessing paramagnetic property due to presence of iron at its centre. Here, we report a label free, rapid and highly sensitive magnetic field based ultra-thin layer chromatography (UTLC) coupled with surface enhanced Raman spectroscopy (SERS) technique for detection and separation of hemozoin from a bacterial mixture. Highly optimized silver nanorods chip fabricated using glancing angle deposition (GLAD) is explored for the UTLC-SERS separation. These chips possessing channel like characteristic and high surface to the volume ratio serve as excellent UTLC plates. The magnetic nature of hemozoin has been exploited for its separation from the mixture of P. aeruginosa (Gram-negative) and S. aureus (Gram-positive) by allocating a 0.6 T magnet over the UTLC flow setup. The solvent front migrated approximately to a distance of 13 mm from the sample point due to the magnetic environment. Spatially resolved SERS data was collected along the mobile phase and separation of mixture was confirmed. Further, staining of hemozoin, P. aeruginosa and S. aureus was done using methylene blue, acridine orange and rhodamine 6 G respectively. The separation was confirmed for the stained analytes. The present developed method provides plate height as low as 18 µm and hemozoin detection limit as <10 parasites/mL. Therefore, we establish a highly specific and sensitive technique capable of separating small amounts of bioanalytes, aiding in the removal of co-infections from the disease at a very early stage of infection.

A simple polystyrene microfluidic device for sensitive and accurate SERS-based detection of infection by malaria parasites

Early and accurate detection of infection by pathogenic microorganisms, such as Plasmodium, the causative agent of malaria, is critical for clinical diagnosis and ultimately determines the patient's outcome. We have combined a polystyrene-based microfluidic device with an immunoassay which utilises Surface-Enhanced Raman Spectroscopy (SERS) to detect malaria. The method can be easily translated to a point-of-care testing format and shows excellent sensitivity and specificity, when compared to the gold standard for laboratorial detection of Plasmodium infections. The device can be fabricated in less than 30 min by direct patterning on shrinkable polystyrene sheets of adaptable three-dimensional microfluidic chips. To validate the microfluidic system, samples of P. falciparum-infected red blood cell cultures were used. The SERS-based immunoassay enabled the detection of 0.0012 ± 0.0001% parasitaemia in a P. falciparum-infected red blood cell culture supernatant, an ∼7-fold higher sensitivity than that attained by most rapid diagnostic tests. Our approach successfully overcomes the main challenges of the current Plasmodium detection methods, including increased reproducibility, sensitivity, and specificity. Furthermore, our system can be easily adapted for detection of other pathogens and has excellent properties for early diagnosis of infectious diseases, a decisive step towards lowering their high burden on healthcare systems worldwide.

Automated wide-field malaria parasite infection detection using Fourier ptychography on stain-free thin-smears

Diagnosis of malaria in endemic areas is hampered by the lack of a rapid, stain-free and sensitive method to directly identify parasites in peripheral blood. Herein, we report the use of Fourier ptychography to generate wide-field high-resolution quantitative phase images of erythrocytes infected with malaria parasites, from a whole blood sample. We are able to image thousands of erythrocytes (red blood cells) in a single field of view and make a determination of infection status of the quantitative phase image of each segmented cell based on machine learning (random forest) and deep learning (VGG16) models. Our random forest model makes use of morphology and texture based features of the quantitative phase images. In order to label the quantitative images of the cells as either infected or uninfected before training the models, we make use of a Plasmodium berghei strain expressing GFP (green fluorescent protein) in all life cycle stages. By overlaying the fluorescence image with the quantitative phase image we could identify the infected subpopulation of erythrocytes for labelling purposes. Our machine learning model (random forest) achieved 91% specificity and 72% sensitivity while our deep learning model (VGG16) achieved 98% specificity and 57% sensitivity. These results highlight the potential for quantitative phase imaging coupled with artificial intelligence to develop an easy to use platform for the rapid and sensitive diagnosis of malaria.

Discriminant Analysis PCA-LDA Assisted Surface-Enhanced Raman Spectroscopy for Direct Identification of Malaria-Infected Red Blood Cells

Various methods for detecting malaria have been developed in recent years, each with its own set of advantages. These methods include microscopic, antigen-based, and molecular-based analysis of blood samples. This study aimed to develop a new, alternative procedure for clinical use by using a large data set of surface-enhanced Raman spectra to distinguish normal and infected red blood cells. PCA-LDA algorithms were used to produce models for separating P. falciparum (3D7)-infected red blood cells and normal red blood cells based on their Raman spectra. Both average normalized spectra and spectral imaging were considered. However, these initial spectra could hardly differentiate normal cells from the infected cells. Then, discrimination analysis was applied to assist in the classification and visualization of the different spectral data sets. The results showed a clear separation in the PCA-LDA coordinate. A blind test was also carried out to evaluate the efficiency of the PCA-LDA separation model and achieved a prediction accuracy of up to 80%. Considering that the PCA-LDA separation accuracy will improve when a larger set of training data is incorporated into the existing database, the proposed method could be highly effective for the identification of malaria-infected red blood cells.

Selenium Vacancies and Synergistic Effect of Near- and Far-Field-Enabled Ultrasensitive Surface-Enhanced Raman-Scattering-Active Substrates for Malaria Detection

Defect engineering with the active control of defect states brings remarkable enhancement on surface-enhanced Raman scattering (SERS) by magnifying semiconductor-molecule interaction. Such light-trapping architectures can increase the light path length, which promotes photon-analytes interactions and further improves the SERS sensitivity. However, by far the reported semiconductor SERS-active substrates based on these strategies are often nonuniform and commonly in the form of isolated laminates or random clusters, which limit their reliability and stability for practical applications. Herein, we develop self-grown single-crystalline "V-shape" SnSe_2-x (SnSe_1.5, SnSe_1.75, SnSe₂) nanoflake arrays (SnSe_2-x NFAs) with controlled selenium vacancies over large-area (10 cm × 10 cm) for ultrahigh-sensitivity SERS. First-principles density functional theory (DFT) is used to calculate the band gap and the electronic density of states (DOS). Based on the Herzberg-Teller theory regarding the vibronic coupling, the results of theoretical calculation reveal that the downshift of band edge and high DOS of SnSe_1.75 can effectively enhance the vibronic coupling within the SnSe_1.75-R6G system, which in turn enhances the photoinduced charge transfer resonance and contributes to the SERS activity with a remarkable enhancement factor of 1.68 × 10⁷. Furthermore, we propose and demonstrate ultrasensitive (10^-15 M for R6G), uniform, and reliable SERS substrates by forming SnSe_1.75 NFAs/Au heterostructures via a facile Au evaporation process. We attribute the superior performance of our SnSe_1.75 NFAs/Au heterostructures to the following reasons: (1) selenium vacancies and (2) synergistic effect of the near and far fields. In addition, we successfully build a detection platform to achieve rapid (∼15 min for the whole process), antibody-free, in situ, and reliable early malaria detection (100% detection rate for 10 samples with 160 points) in whole blood, and molecular hemozoin (<100/mL) can be detected. Our approach not only provides an efficient technique to obtain large-area, uniform, and reliable SERS-active substrates but also offers a substantial impact on addressing practical issues in many application scenarios such as the detection of insect-borne infectious diseases.

A review of surface-enhanced Raman spectroscopy in pathological processes

With the continuous growth of the human population and new challenges in the quality of life, it is more important than ever to diagnose diseases and pathologies with high accuracy, sensitivity and in different scenarios from medical implants to the operation room. Although conventional methods of diagnosis revolutionized healthcare, alternative analytical methods are making their way out of academic labs into clinics. In this regard, surface-enhanced Raman spectroscopy (SERS) developed immensely with its capability to achieve single-molecule sensitivity and high-specificity in the last two decades, and now it is well on its way to join the arsenal of physicians. This review discusses how SERS is becoming an essential tool for the clinical investigation of pathologies including inflammation, infections, necrosis/apoptosis, hypoxia, and tumors. We critically discuss the strategies reported so far in nanoparticle assembly, functionalization, non-metallic substrates, colloidal solutions and how these techniques improve SERS characteristics during pathology diagnoses like sensitivity, selectivity, and detection limit. Moreover, it is crucial to introduce the most recent developments and future perspectives of SERS as a biomedical analytical method. We finally discuss the challenges that remain as bottlenecks for a routine SERS implementation in the medical room from in vitro to in vivo applications. The review showcases the adaptability and versatility of SERS to resolve pathological processes by covering various experimental and analytical methods and the specific spectral features and analysis results achieved by these methods.

Raman spectroscopic analysis of skin as a diagnostic tool for Human African Trypanosomiasis

Human African Trypanosomiasis (HAT) has been responsible for several deadly epidemics throughout the 20th century, but a renewed commitment to disease control has significantly reduced new cases and motivated a target for the elimination of Trypanosoma brucei gambiense-HAT by 2030. However, the recent identification of latent human infections, and the detection of trypanosomes in extravascular tissues hidden from current diagnostic tools, such as the skin, has added new complexity to identifying infected individuals. New and improved diagnostic tests to detect Trypanosoma brucei infection by interrogating the skin are therefore needed. Recent advances have improved the cost, sensitivity and portability of Raman spectroscopy technology for non-invasive medical diagnostics, making it an attractive tool for gambiense-HAT detection. The aim of this work was to assess and develop a new non-invasive diagnostic method for T. brucei through Raman spectroscopy of the skin. Infections were performed in an established murine disease model using the animal-infective Trypanosoma brucei brucei subspecies. The skin of infected and matched control mice was scrutinized ex vivo using a confocal Raman microscope with 532 nm excitation and in situ at 785 nm excitation with a portable field-compatible instrument. Spectral evaluation and Principal Component Analysis confirmed discrimination of T. brucei-infected from uninfected tissue, and a characterisation of biochemical changes in lipids and proteins in parasite-infected skin indicated by prominent Raman peak intensities was performed. This study is the first to demonstrate the application of Raman spectroscopy for the detection of T. brucei by targeting the skin of the host. The technique has significant potential to discriminate between infected and non-infected tissue and could represent a unique, non-invasive diagnostic tool in the goal for elimination of gambiense-HAT as well as for Animal African Trypanosomiasis (AAT).

Human African Trypanosomiasis (HAT), also known as sleeping sickness, is a disease caused by the parasite Trypanosoma brucei and has been responsible for the death of millions of people across Africa in the 20^th century. It is also a major economic burden for countries endemic for trypanosomiasis, affecting livestock productivity in rural areas (Animal African Trypanosomiasis). A long-term international collaboration with the help of the World Health Organisation has resulted in the rate of human infection decreasing to less than 1000 new cases per year. However, the human disease continues to spread within remote villages. Current diagnosis is based on the detection of parasites in blood and serum samples, but this is challenging during chronic human infections with low or non-detectable parasitaemia. However, the recent discovery of extravascular skin-dwelling trypanosomes indicates that a reservoir of infection remains undetected, threatening the effort to eliminate the disease. In this study we have targeted the skin as a site for diagnosis using Raman spectroscopy and demonstrate that this method showed great promise in the laboratory, laying the foundation for field studies to examine its potential to strengthen current diagnostic strategies for detecting HAT cases.

The Role of Raman Spectroscopy Within Quantitative Metabolomics

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.

The application of spectroscopy techniques for diagnosis of malaria parasites and arboviruses and surveillance of mosquito vectors: A systematic review and critical appraisal of evidence

CONCLUSIONS/SIGNIFICANCE

The potential of RS as a surveillance tool for malaria and arbovirus vectors and MIRS for the diagnosis and surveillance of arboviruses is yet to be assessed. NIRS capacity as a surveillance tool for malaria and arbovirus vectors should be validated under field conditions, and its potential as a diagnostic tool for malaria and arboviruses needs to be evaluated. It is recommended that all 3 techniques evaluated simultaneously using multiple machine learning techniques in multiple epidemiological settings to determine the most accurate technique for each application. Prior to their field application, a standardised protocol for spectra collection and data analysis should be developed. This will harmonise their application in multiple field settings allowing easy and faster integration into existing disease control platforms. Ultimately, development of rapid and cost-effective point-of-care diagnostic tools for malaria and arboviruses based on spectroscopy techniques may help combat current and future outbreaks of these infectious diseases.

Portable Impedance Analyzer as a Rapid Screening Tool for Malaria: An Experimental Study With Culture and Blood Infected Samples by Early Forms of Plasmodium Falciparum

Infection by the parasite of malaria is a serious healthcare problem for populations residing primarily in tropical and subtropical countries. Early detection of the disease is essential to reduce both the mortality rate and spreading of the disease in the infected areas. Current methods for malaria diagnosis still rely on microscopic analysis of blood smears, which is a time-consuming and expensive process, in addition of requiring trained examiners to perform the analysis. In this paper, we introduce a novel fast screening tool for malaria based on a portable blood impedance analyzer. The simultaneous multi-tone injection of current and voltage detection of the device allow reducing the screening time (order of seconds) while enhancing the differences in impedance signal registered among frequencies to increase parasitemia level discrimination. We went further to demonstrate the possibility of directly applying the device on blood samples collected from volunteers to distinguish between infected and non-infected samples. Minimum parasitemia level discriminated was 0.0078% (or, equivalently 390 parasites/μl), which closely approaches the international standard set to 200 parasites/μl. Finally, we also show the frequency dependency of ring-synchronized and unsynchronized blood samples, which can constitute the basis for development of a point-of-care and laboratory-free method to distinguish different stages of malaria infection in economic stagnated communities.

Antibody-free rapid diagnosis of malaria in whole blood with surface-enhanced Raman Spectroscopy using Nanostructured Gold Substrate

PURPOSE

The aim of this study is to establish a rapid antibody-free diagnostic method of malaria infection with Plasmodium falciparum and Plasmodium vivax in whole blood with Surface-enhanced Raman Spectroscopy using Nanostructured Gold Substrate.

MATERIALS AND METHODS

The blood samples collected from patients were first lysed and centrifuged before dropping on the gold nano-structure (AuNS) substrate. Malaria diagnosis was performed by detecting Raman peaks from Surface Enhanced Raman Spectroscopy (SERS) with a 532 nm laser excitation.

RESULTS

Raman peaks at 1370 cm-1, 1570 cm-1, and 1627 cm-1, known to have high specificity against interference from other mosquito-borne diseases such as Dengue and West Nile virus infection, were selected as the fingerprint markers associated with P. falciparum and P. vivax infection. The limit of detection was 10-5 dilution, corresponding to the concentration of parasitized blood cells of 100/mL. A total number of 25 clinical samples, including 5 from patients with P. falciparum infection, 10 with P. vivax infection and 10 from healthy volunteers, were evaluated to support its clinical practical use. The whole assay on malaria detection took 30 min to complete.

CONCLUSIONS

While the samples analyzed in this work have strong clinical relevance, we have clearly demonstrated that sensitive malaria detection using AuNS-SERS is a practical direction for rapid in-field diagnosis of malaria infection.

Confocal Raman Spectral Imaging Study of DAPT, a γ-secretase Inhibitor, Induced Physiological and Biochemical Reponses in Osteosarcoma Cells

Confocal Raman microspectral imaging was adopted to elucidate the cellular drug responses of osteosarcoma cells (OC) to N-[N-(3, 5-difluorophenyl acetyl)-L-alanyl]-sphenylglycine butyl ester (DAPT), a γ-secretase inhibitor, by identifying the drug induced subcellular compositional and structural changes. Methods: Spectral information were acquired from cultured osteosarcoma cells treated with 0 (Untreated Group, UT), 10 (10 μM DAPT treated, 10T), 20 μM (20 μM DAPT treated, 20T) DAPT for 24 hours. A one-way ANOVA and Tukey's honest significant difference (HSD) post hoc multiple test were sequentially applied to address spectral features among three groups. Multivariate algorithms such as K-means clustering analysis (KCA) and Principal component analysis (PCA) were used to highlight the structural and compositional differences, while, univariate imaging was applied to illustrate the distribution pattern of certain cellular components after drug treatment. Results: Major biochemical changes in DAPT-induced apoptosis came from changes in the content and structure of proteins, lipids, and nucleic acids. By adopted multivariate algorithms, the drug induced cellular changes was identified by the morphology and spectral characteristics between untreated cells and treated cells, testified that DAPT mainly acted in the nuclear region. With the increase of the drug concentration, the content of main subcellular compositions, such nucleic acid, protein, and lipid decreased. In an addition, DAPT-induced nuclear fragmentation and apoptosis was depicted by the univariate Raman image of major cellular components (nucleic acids, proteins and lipids). Conclusions: The achieved Raman spectral and imaging results illustrated detailed DAPT-induced subcellular compositional and structural variations as a function of drug dose. Such observations can not only explain drug therapeutic mechanisms of OC DAPT treatment, and also provide new insights for accessing the medicine curative efficacy and predicting prognosis.

SERS Platform for Dengue Diagnosis from Clinical Samples Employing a Hand Held Raman Spectrometer

Dengue is a serious global health concern especially in tropical and subtropical countries. About 2.5 billion of the world's population is at risk for dengue infection. Early diagnosis is the key to prevent the deterioration of health of the patient to severe illness. Laboratory diagnosis of dengue is essential for providing appropriate supportive treatment to dengue patients with febrile illness, which is difficult to diagnose clinically. Here, we demonstrate surface enhanced Raman scattering (SERS) based diagnosis of dengue virus in clinical blood samples collected from total of 102 subjects. All of the samples were well characterized by conventional NS1 antigen and IgM antibody ELISA kits. The silver nanorods array fabricated by glancing angle deposition technique were employed as SERS substrates. A small amount of patient blood serum (5 μL) was taken for analysis and the report was prepared within a minute. SERS spectra of pure NS1 protein as well as spiked in serum was also recorded separately. Principal component analysis (PCA) was employed as the statistical tool to differentiate dengue positive, dengue negative, and healthy subjects on the basis of their respective SERS spectra. This method provides a sensitive, rapid, and field deployable diagnosis of dengue at the early stage (within 5 days of the onset of symptoms).

Diagnosis of Malaria Parasites Plasmodium spp. in Endemic Areas: Current Strategies for an Ancient Disease

Fast and effective detection of the causative agent of malaria in humans, protozoan Plasmodium parasites, is of crucial importance for increasing the effectiveness of treatment and to control a devastating disease that affects millions of people living in endemic areas. The microscopic examination of Giemsa-stained blood films still remains the gold-standard in Plasmodium detection today. However, there is a high demand for alternative diagnostic methods that are simple, fast, highly sensitive, ideally do not rely on blood-drawing and can potentially be conducted by the patients themselves. Here, the history of Plasmodium detection is discussed, and advantages and disadvantages of diagnostic methods that are currently being applied are assessed.

Whole-Organism Analysis by Vibrational Spectroscopy

Vibrational spectroscopy has contributed to the understanding of biological materials for many years. As the technology has advanced, the technique has been brought to bear on the analysis of whole organisms. Here, we discuss advanced and recently developed infrared and Raman spectroscopic instrumentation to whole-organism analysis. We highlight many of the recent contributions made in this relatively new area of spectroscopy, particularly addressing organisms associated with disease with emphasis on diagnosis and treatment. The application of vibrational spectroscopic techniques to entire organisms is still in its infancy, but new developments in imaging and chemometric processing will likely expand in the field in the near future.

Ag Nanorods-Based Surface-Enhanced Raman Scattering: Synthesis, Quantitative Analysis Strategies, and Applications

Surface-Enhanced Raman Scattering (SERS) is a powerful technology that provides abundant chemical fingerprint information with advantages of high sensitivity and time-saving. Advancements in SERS substrates fabrication allow Ag nanorods (AgNRs) possess superior sensitivity, high uniformity, and excellent reproducibility. To further promote AgNRs as a promising SERS substrate candidate to a broader application scope, oxides are integrated with AgNRs by virtue of their unique properties which endow the AgNRs-oxide hybrid with high stability and recyclability. Aside from SERS substrates fabrication, significant developments in quantitative analysis strategies offer enormous approaches to minimize influences resulted from variations of measuring conditions and to provide the reasonable data analysis. In this review, we discuss various fabrication approaches for AgNRs and AgNRs-oxide hybrids to achieve efficient SERS platforms. Then, we introduce three types of strategies which are commonly employed in chemical quantitative analysis to reach a reliable result. Further, we highlight SERS applications including food safety, environment safety, biosensing, and vapor sensing, demonstrating the potential of SERS as a powerful and promising technique. Finally, we conclude with the current challenges and future prospects toward efficient SERS manipulations for broader real-world applications.

Recent Advancement in the Surface-Enhanced Raman Spectroscopy-Based Biosensors for Infectious Disease Diagnosis

Diagnosis is the key component in disease elimination to improve global health. However, there is a tremendous need for diagnostic innovation for neglected tropical diseases that largely consist of mosquito-borne infections and bacterial infections. Early diagnosis of these infectious diseases is critical but challenging because the biomarkers are present at low concentrations, demanding bioanalytical techniques that can deliver high sensitivity with ensured specificity. Owing to the plasmonic nanomaterials-enabled high detection sensitivities, even up to single molecules, surface-enhanced Raman spectroscopy (SERS) has gained attention as an optical analytical tool for early disease biomarker detection. In this mini-review, we highlight the SERS-based assay development tailored to detect key types of biomarkers for mosquito-borne and bacterial infections. We discuss in detail the variations of SERS-based techniques that have developed to afford qualitative and quantitative disease biomarker detection in a more accurate, affordable, and field-transferable manner. Current and emerging challenges in the advancement of SERS-based technologies from the proof-of-concept phase to the point-of-care phase are also briefly discussed.

Surface-enhanced Raman spectroscopy of microorganisms: limitations and applicability on the single-cell level

Detection and characterization of microorganisms is essential for both clinical diagnostics and environmental studies. An emerging technique to analyse microbes at single-cell resolution is surface-enhanced Raman spectroscopy (surface-enhanced Raman scattering: SERS). Optimised SERS procedures enable fast analytical read-outs with specific molecular information, providing insight into the chemical composition of microbiological samples. Knowledge about the origin of microbial SERS signals and parameter(s) affecting their occurrence, intensity and/or reproducibility is crucial for reliable SERS-based analyses. In this work, we explore the feasibility and limitations of the SERS approach for characterizing microbial cells and investigate the applicability of SERS for single-cell sorting as well as for three-dimensional visualization of microbial communities. Analyses of six different microbial species (an archaeon, two Gram-positive bacteria, three Gram-negative bacteria) showed that for several of these organisms distinct features in their SERS spectra were lacking. As additional confounding factor, the physiological conditions of the cells (as influenced by e.g., storage conditions or deuterium-labelling) were systematically addressed, for which we conclude that the respective SERS signal at the single-cell level is strongly influenced by the metabolic activity of the analysed cells. While this finding complicates the interpretation of SERS data, it may on the other hand enable probing of the metabolic state of individual cells within microbial populations of interest.

Inorganic Complexes and Metal-Based Nanomaterials for Infectious Disease Diagnostics

Infectious diseases claim millions of lives each year. Robust and accurate diagnostics are essential tools for identifying those who are at risk and in need of treatment in low-resource settings. Inorganic complexes and metal-based nanomaterials continue to drive the development of diagnostic platforms and strategies that enable infectious disease detection in low-resource settings. In this review, we highlight works from the past 20 years in which inorganic chemistry and nanotechnology were implemented in each of the core components that make up a diagnostic test. First, we present how inorganic biomarkers and their properties are leveraged for infectious disease detection. In the following section, we detail metal-based technologies that have been employed for sample preparation and biomarker isolation from sample matrices. We then describe how inorganic- and nanomaterial-based probes have been utilized in point-of-care diagnostics for signal generation. The following section discusses instrumentation for signal readout in resource-limited settings. Next, we highlight the detection of nucleic acids at the point of care as an emerging application of inorganic chemistry. Lastly, we consider the challenges that remain for translation of the aforementioned diagnostic platforms to low-resource settings.

Raman characterizations of red blood cells with β-thalassemia using laser tweezers Raman spectroscopy

This study aimed to study the differences in Raman spectra of red blood cells (RBCs) among patients with β-thalassemia and controls using laser tweezers Raman spectroscopy (LTRS) system.A total of 33 patients with β-thalassemia major, 49 with β-thalassemia minor, and 65 controls were studied. Raman spectra of RBCs for each sample were recorded. Principal component analysis (PCA), one-way analysis of variance (ANOVA), and independent-sample t test were performed.The intensities of Raman spectra of β-thalassemia (major and minor) RBCs were lower than those of controls, especially at bands 1546, 1603, and 1619 cm. The intensity ratio of band 1546 cm to band 1448 cm demonstrated that there was a significant difference between the spectra of β-thalassemia major (mostly below 2.15) and those of controls. The spectra of controls could be well distinguished from those of β-thalassemia major using PCA. After normalization, the spectra of two different genotypes with β/β mutations mainly overlapped, while those with β/β mutations had lower intensity at bands 1546, 1603, and 1619 cm.The present study provided Raman characteristics of RBCs in patients with β-thalassemia major and supported the use of LTRS as a method for screening β-thalassemia major. The recognition rate for β-thalassemia minor needs to be further improved.

Image analysis and machine learning for detecting malaria

Malaria remains a major burden on global health, with roughly 200 million cases worldwide and more than 400,000 deaths per year. Besides biomedical research and political efforts, modern information technology is playing a key role in many attempts at fighting the disease. One of the barriers toward a successful mortality reduction has been inadequate malaria diagnosis in particular. To improve diagnosis, image analysis software and machine learning methods have been used to quantify parasitemia in microscopic blood slides. This article gives an overview of these techniques and discusses the current developments in image analysis and machine learning for microscopic malaria diagnosis. We organize the different approaches published in the literature according to the techniques used for imaging, image preprocessing, parasite detection and cell segmentation, feature computation, and automatic cell classification. Readers will find the different techniques listed in tables, with the relevant articles cited next to them, for both thin and thick blood smear images. We also discussed the latest developments in sections devoted to deep learning and smartphone technology for future malaria diagnosis.

A pilot study on fingerprinting Leishmania species from the Old World using Fourier transform infrared spectroscopy

Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains’ hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens.

Graphical abstract

Recent Progress in the Development of Diagnostic Tests for Malaria

The impact of malaria on global health has continually prompted the need to develop effective diagnostic strategies. In malaria endemic regions, routine diagnosis is hampered by technical and infrastructural challenges to laboratories. These laboratories lack standard facilities, expertise or diagnostic supplies; thus, therapy is administered based on clinical or self-diagnosis. There is the need for accurate diagnosis of malaria due to the continuous increase in the cost of medication, and the emergence and spread of drug resistant strains. However, the widely utilized Giemsa-stained microscopy and immunochromatographic tests for malaria are liable to several drawbacks, including inadequate sensitivity and false-positive outcomes. Alternative methods that offer improvements in performance are either expensive, have longer turnaround time or require a level of expertise that makes them unsuitable for point-of-care (POC) applications. These gaps necessitate exploration of more efficient detection techniques with the potential of POC applications, especially in resource-limited settings. This minireview discusses some of the recent trends and new approaches that are seeking to improve the clinical diagnosis of malaria.

Surface-enhanced Raman spectroscopy of blood serum based on gold nanoparticles for the diagnosis of the oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is becoming more common across the globe. The prognosis of OSCC is largely dependent on the early detection. But the routine oral cavity examination may delay the diagnosis because the early oral malignant lesions may be clinically indistinguishable from benign or inflammatory diseases. In this study, the new diagnostic method is developed by using the surface enhanced Raman spectroscopy (SERS) to detect the serum samples from the cancer patients.

METHOD

The blood serum samples were collected from the OSCC patients, MEC patients and the volunteers without OSCC or MEC. Gold nanoparticles(NPs) were then mixed in the serum samples to obtain the high quality SERS spectra. There were totally 135 spectra of OSCC, 90 spectra of mucoepidermoid carcinoma (MEC) and 145 spectra of normal control group, which were captured by SERS successfully. Compared with the normal control group, the Raman spectral differences exhibited in the spectra of OSCC and MEC groups, which were assigned to the nucleic acids, proteins and lipids. Based on these spectral differences and features, the algorithms of principal component analysis(PCA) and linear discriminant analysis (LDA) were employed to analyze and classify the Raman spectra of different groups.

RESULTS

Compared with the normal groups, the major increased peaks in the OSCC and MEC groups were assigned to the molecular structures of the nucleic acids and proteins. And these different major peaks between the OSCC and MEC groups were assigned to the special molecular structures of the carotenoids and lipids. The PCA-LDA results demonstrated that OSCC could be discriminated successfully from the normal control groups with a sensitivity of 80.7% and a specificity of 84.1%. The process of the cross validation proved the results analyzed by PCA-LDA were reliable.

CONCLUSION

The gold NPs were appropriate substances to capture the high-quality SERS spectra of the OSCC, MEC and normal serum samples. The results of this study confirm that SERS combined PCA-LDA had a giant capability to detect and diagnosis OSCC through the serum sample successfully.

A primary SERS-active interconnected Si-nanocore network for biomolecule detection with plasmonic nanosatellites as a secondary boosting mechanism

We report in this study, the development of a polymorphic biosensitive Si nanocore superstructure as a SERS biosensing platform.

Fabrication of gold-coated PDMS surfaces with arrayed triangular micro/nanopyramids for use as SERS substrates

Using the tip-based continuous indentation process, arrays of three-dimensional pyramidal cavities have been successfully machined on a copper template and the structures were successfully transferred to a polydimethylsiloxane (PDMS) surface using a reverse nanoimprinting approach. The structured PDMS surface is coated with a thin Au film, and the final substrate is demonstrated as a surface-enhanced Raman spectroscopy (SERS) substrate. Rhodamine 6G (R6G) was used as a probe molecule in the present study to confirm the SERS measurements. Arrays of micro/nanostructures of different dimensions were formed by the overlap of pyramidal cavities with different adjacent distances using the tip-based continuous indentation process. The effects of the reverse nanoimprinting process and coating process on the final topography of the structures are studied. The experimental results show that the Raman intensity of the Au-film-coated PDMS substrate is influenced by the topography of the micro/nanostructures and by the thickness of the Au film. The Raman intensity of 1362 cm^-1 R6G peak on the structured Au-film-coated PDMS substrate is about 8 times higher than the SERS tests on a commercial substrate (Q-SERS). A SERS enhancement factor ranging from 7.5 × 10⁵ to 6 × 10⁶ was achieved using the structured Au-film-coated PDMS surface, and it was demonstrated that the method proposed in this paper is reliable, replicable, homogeneous and low-cost for the fabrication of SERS substrates.