A label-free cellulose SERS biosensor chip with improvement of nanoparticle-enhanced LSPR effects for early diagnosis of subarachnoid hemorrhage-induced complications

Paper-based substrates for surface-enhanced Raman spectroscopy sensing

Surface-enhanced Raman scattering (SERS) has been recognized as one of the most sensitive analytical methods by adsorbing the target of interest onto a plasmonic surface. Growing attention has been directed towards the fabrication of various substrates to broaden SERS applications. Among these, flexible SERS substrates, particularly paper-based ones, have gained popularity due to their easy-to-use features by full contact with the sample surface. Herein, we reviewed the latest advancements in flexible SERS substrates, with a focus on paper-based substrates. Firstly, it begins by introducing various methods for preparing paper-based substrates and highlights their advantages through several illustrative examples. Subsequently, we demonstrated the booming applications of these paper-based SERS substrates in abiotic and biological matrix detection, with particular emphasis on their potential application in clinical diagnosis. Finally, the prospects and challenges of paper-based SERS substrates in broader applications are discussed.

Constructing a Ring-like Self-Aggregation SERS Sensor with the Coffee Ring Effect for Ultrasensitive Detection and Photocatalytic Degradation of the Herbicides Paraquat and Diquat

A strategy for building ring-like deposit surface-enhanced Raman scattering (SERS) sensors with the coffee ring effect through the functional modification of the silica nanoparticle surface encapsulated by free-tagged Ag nanoparticles is addressed along with their applications in the SERS-based detection and degradation of target species, including paraquat, diquat, and their free radicals. The nanogap formed by two interparticles with SERS hotspots provides a gigantic amplification signal for the Raman scattering intensity of the analyte molecule located approximately at the hotspots. The enhanced Raman spectrum signals of these target analytes were achieved through the hotspot region of the surface plasmon resonance (SPR) located on the embankment formed by self-aggregation of SiO₂@Ag nanoparticles due to the coffee ring effect. Meanwhile, the intrinsic properties of Ag nanoparticles embedded onto the silica surface were applied to photocatalytically degrade the target analytes by harvesting energy from sunlight. The SERS sensor detected the analytes down to 10^-9 M in the aqueous solution.

Flexible surface-enhanced Raman scatting substrates: recent advances in their principles, design strategies, diversified material selections and applications

Surface-enhanced Raman scattering (SERS) is widely used as a powerful analytical technology in cutting-edge areas such as food safety, biology, chemistry, and medical diagnosis, providing ultra-fast, ultra-sensitive, nondestructive characterization and achieving ultra-high detection sensitivity even down to the single-molecule level. Development of Raman spectroscopy is strongly dependent on high-performance SERS substrates, which have long evolved from the early days of rough metal electrodes to periodic nanopatterned arrays building on solid supporting substrates. For rigid SERS substrates, however, their applications are restricted by sophisticated pretreatments for detecting solid samples with non-planar surfaces. It is therefore essential to reassert the principles in constructing flexible SERS substrates. Herein, we comprehensively review the state-of-the-art in understanding, preparing and using flexible SERS. The basic mechanisms behind the flexible SERS are briefly outlined, typical design strategies are highlighted and diversified selection of materials in preparing flexible SERS substrates are reviewed. Then the recent achievements of various interdisciplinary applications based on flexible SERS substrates are summarized. Finally, the challenges and perspectives for future evolution of flexible SERS and their applications are demonstrated. We propose new research directions focused on stimulating the real potential of SERS as an advanced analytical technique for commercialization.

Active Opto-Magnetic Biosensing with Silicon Microring Resonators

Integrated optical biosensors are gaining increasing attention for their exploitation in lab-on-chip platforms. The standard detection method is based on the measurement of the shift of some optical quantity induced by the immobilization of target molecules at the surface of an integrated optical element upon biomolecular recognition. However, this requires the acquisition of said quantity over the whole hybridization process, which can take hours, during which any external perturbation (e.g., temperature and mechanical instability) can seriously affect the measurement and contribute to a sizeable percentage of invalid tests. Here, we present a different assay concept, named Opto-Magnetic biosensing, allowing us to optically measure off-line (i.e., post hybridization) tiny variations of the effective refractive index seen by microring resonators upon immobilization of magnetic nanoparticles labelling target molecules. Bound magnetic nanoparticles are driven in oscillation by an external AC magnetic field and the corresponding modulation of the microring transfer function, due to the effective refractive index dependence on the position of the particles above the ring, is recorded using a lock-in technique. For a model system of DNA biomolecular recognition we reached a lowest detected concentration on the order of 10 pm, and data analysis shows an expected effective refractive index variation limit of detection of 7.5×10-9 RIU, in a measurement time of just a few seconds.

Raman, Infrared and Brillouin Spectroscopies of Biofluids for Medical Diagnostics and for Detection of Biomarkers

This review surveys Infrared, Raman/SERS and Brillouin spectroscopies for medical diagnostics and detection of biomarkers in biofluids, that include urine, blood, saliva and other biofluids. These optical sensing techniques are non-contact, noninvasive and relatively rapid, accurate, label-free and affordable. However, those techniques still have to overcome some challenges to be widely adopted in routine clinical diagnostics. This review summarizes and provides insights on recent advancements in research within the field of vibrational spectroscopy for medical diagnostics and its use in detection of many health conditions such as kidney injury, cancers, cardiovascular and infectious diseases. The six comprehensive tables in the review and four tables in supplementary information summarize a few dozen experimental papers in terms of such analytical parameters as limit of detection, range, diagnostic sensitivity and specificity, and other figures of merits. Critical comparison between SERS and FTIR methods of analysis reveals that on average the reported sensitivity for biomarkers in biofluids for SERS vs FTIR is about 103 to 105 times higher, since LOD SERS are lower than LOD FTIR by about this factor. High sensitivity gives SERS an edge in detection of many biomarkers present in biofluids at low concentration (nM and sub nM), which can be particularly advantageous for example in early diagnostics of cancer or viral infections.HighlightsRaman, Infrared spectroscopies use low volume of biofluidic samples, little sample preparation, fast time of analysis and relatively inexpensive instrumentation.Applications of SERS may be a bit more complicated than applications of FTIR (e.g., limited shelf life for nanoparticles and substrates, etc.), but this can be generously compensated by much higher (by several order of magnitude) sensitivity in comparison to FTIR.High sensitivity makes SERS a noninvasive analytical method of choice for detection, quantification and diagnostics of many health conditions, metabolites, and drugs, particularly in diagnostics of cancer, including diagnostics of its early stages.FTIR, particularly ATR-FTIR can be a method of choice for efficient sensing of many biomarkers, present in urine, blood and other biofluids at sufficiently high concentrations (mM and even a few µM)Brillouin scattering spectroscopy detecting visco-elastic properties of probed liquid medium, may also find application in clinical analysis of some biofluids, such as cerebrospinal fluid and urine.

Application of surface-enhanced Raman spectroscopy as a diagnostic system for the highly sensitive monitoring of the evolution of subarachnoid hemorrhage-induced complications

A novel SERS biosensor to detect the development of SAH and its induced complications from cerebrospinal fluid is reported.

Facile fabrication of Ag@C@C8 nanoparticles as a SERS substrate and their environmental applications

Carbon-coated silver (Ag@C) nanoparticles were prepared by a one-step hydrothermal synthesis method, the surface was modified with chlorodimethyloctylsilane (C8) to generate C8 functionalized Ag@C@C8 nanoparticles with long-term stability and high sensitivity.

SERS-based immunoassay based on gold nanostars modified with 5,5'-dithiobis-2-nitrobenzoic acid for determination of glial fibrillary acidic protein

A surface-enhanced Raman scattering (SERS)-based immunoassay with gold nanostars (GNSs) is utilized for determination of the subarachnoid hemorrhage (SAH) biomarker glial fibrillary acidic protein (GFAP) at very low concentration levels, which allows for early diagnosis and guides clinical decision-making to treat SAH-induced complications. The Raman reporter 5,5'-dithiobis-2-nitrobenzoic acid (DTNB) modified on GNSs was selected as the SERS tags. The SERS immunoassay was assembled by SERS tag and GFAP probe-immobilized ITO substrate. Therefore, the level of GFAP can be detected by monitoring the characteristic Raman peak intensity of GFAP-conjugated GNSs at 1332 cm^-1 with a very low detection limit. Under optimized conditions, the assay can work in the GFAP concentration range from 1 pg⋅mL^-1 to 1 μg⋅mL^-1, with a detection limit as low as 0.54 fg⋅mL^-1. The performance of the SERS immunoassay proven by the detection of GFAP is equivalent to that of the conventional enzyme-linked immunosorbent assay (ELISA). Scheme 1. Schematic illustration of GNSs SERS immunoassay for ultrasensitive dynamic change detection of GFAP. (SAH: Subarachnoid hemorrhage, SCF: Cerebrospinal fluid; GNSs: gold nanostars; SERS: surface-enhanced Raman scattering; GFAP: glial fibrillary acidic protein).

Optical/electrochemical methods for detecting mitochondrial energy metabolism

This review highlights the biological importance of mitochondrial energy metabolism and the applications of multiple optical/electrochemical approaches to determine energy metabolites. Mitochondria, the main sites of oxidative phosphorylation and adenosine triphosphate (ATP) biosynthesis, provide the majority of energy required by aerobic cells for maintaining their physiological activity. They also participate in cell growth, differentiation, information transmission, and apoptosis. Multiple mitochondrial diseases, caused by internal or external factors, including oxidative stress, intense fluctuations of the ionic concentration, abnormal oxidative phosphorylation, changes in electron transport chain complex enzymes and mutations in mitochondrial DNA, can occur during mitochondrial energy metabolism. Therefore, developing accurate, sensitive, and specific methods for the in vivo and in vitro detection of mitochondrial energy metabolites is of great importance. In this review, we summarise the mitochondrial structure, functions, and crucial energy metabolic signalling pathways. The mechanism and applications of different optical/electrochemical methods are thoroughly reviewed. Finally, future research directions and challenges are proposed.

A biosensing method for the direct serological detection of liver diseases by integrating a SERS-based sensor and a CNN classifier

Direct serological detection, due to its clinical facility and testing economy, affords prominent clinical values to the early detection of cancer. Surface-enhanced Raman spectroscopy (SERS)-based sensors have shown great promise in realizing this form of detection. Detecting liver cancer early with such a form, especially in terms of monitoring the pathogenic progression from hepatic inflammations to cancer, is the most effective clinical path to reducing the mortality rate. However, the methodology investigation for this purpose remains a formidable challenge. We fabricated a SERS-based sensor, consisting of Au-Ag nanocomplex-decorated ZnO nanopillars on paper. The sensor has an analytic enhancement factor of 1.02 × 107, which is enough to sense the biomolecular information of liver diseases through direct serum SERS analysis. A convolutional neural network (CNN) classifier for recognizing serum SERS spectra was constructed by deep learning. Integrating this sensor with the CNN, we established an intelligent biosensing method and realized direct serological detection of liver diseases within 1 min. As a proof-of-concept, the method achieved a prediction accuracy of 97.78% on an independent test dataset randomly sampled from 30 normal controls, 30 hepatocellular carcinoma (HCC) cases, and 30 hepatitis B (HB) patients. The results suggest this method can be developed for detecting liver diseases clinically and is worthy of exploration as a means of liver cancer surveillance. The presented sensor holds potential for clinical translation to the direct serological detection of diseases.

Label-free breast cancer detection using fiber probe-based Raman spectrochemical biomarker-dominated profiles extracted from a mixture analysis algorithm

We report the development of a label-free, simple, and high efficiency breast cancer detection platform with multimodal biomarker analytic algorithms on a portable 785 nm Raman setup with an endoscopic Raman-lensed fiber optic probe. We propose a multimodal biomarker extraction algorithm (PCMA) implemented by combining a multivariate statistics principal component analysis (PCA) algorithm and a multivariate curve resolution-alternating least squares (MCR-ALS) computational model for extraction of the biomarker information hidden in Raman spectrochemical data. We show that the six Raman spectrochemical peaks at 1009, 1270, 1305/1443, 1658, and 1750 cm-1 assigned to phenylalanine, amide III in proteins, CH2 deformation in lipids, amide I in proteins, and carbonyl, respectively, can be used as a biomarker for breast cancer diagnosis using the biomarker-dominated PCMA spectrochemical spectra of breast tissues. From 20 human breast tissues, the PCMA-linear discriminant analysis (PCMA-LDA) identification method achieved high classification performance with a sensitivity and specificity >99% along with an improvement of approximately 4.5% compared to the performance without the PCMA mixture analysis algorithm. Our label-free breast cancer detection method has the potential for clinical application to diagnose breast cancer in real-time during surgery.

Cellulose-Based Flexible Functional Materials for Emerging Intelligent Electronics

There is currently enormous and growing demand for flexible electronics for personalized mobile equipment, human-machine interface units, wearable medical-healthcare systems, and bionic intelligent robots. Cellulose is a well-known natural biopolymer that has multiple advantages including low cost, renewability, easy processability, and biodegradability, as well as appealing mechanical performance, dielectricity, piezoelectricity, and convertibility. Because of its multiple merits, cellulose is frequently used as a substrate, binder, dielectric layer, gel electrolyte, and derived carbon material for flexible electronic devices. Leveraging the advantages of cellulose to design advanced functional materials will have a significant impact on portable intelligent electronics. Herein, the unique molecular structure and nanostructures (nanocrystals, nanofibers, nanosheets, etc.) of cellulose are briefly introduced, the structure-property-application relationships of cellulosic materials summarized, and the processing technologies for fabricating cellulose-based flexible electronics considered. The focus then turns to the recent advances of cellulose-based functional materials toward emerging intelligent electronic devices including flexible sensors, optoelectronic devices, field-effect transistors, nanogenerators, electrochemical energy storage devices, biomimetic electronic skins, and biological detection devices. Finally, an outlook of the potential challenges and future prospects for developing cellulose-based wearable devices and bioelectronic systems is presented.

Evaporation-induced self-assembly of silver nanospheres and gold nanorods on a super-hydrophobic substrate for SERS applications

Surface-enhanced Raman scattering (SERS) has drawn attention for broad applications. We successfully fabricated highly effective SERS structures via evaporation-induced self-assembly of blend nanoparticles containing sliver nanospheres (Ag NSs) and gold nanorods (Au NRs) on a super-hydrophobic (SH) substrate. On the SH substrate, the droplets of the mixed aqueous solution of silver nanospheres (Ag NSs), gold nanorods (Au NRs), and probe molecules can preserve their spherical shape during the evaporation process, and the probe molecules (R6G) are confined into extremely small areas after solvent removal due to hydrophobicity-enhanced concentration effects. The Raman enhancement effect of the blend nanoparticles with 40 vol% Ag NSs is far higher than that of the other samples. The structure of the aggregated Ag NSs on the film-like Au NRs greatly enhances the SERS effect of Ag NSs, which is optimal for the blend system with 40 vol% Ag NSs. The SERS structure also displays excellent signal reproducibility (RSD < 10%) and low detection limits (0.5 nM). Thus, this work offers a simple and efficient strategy to fabricate a highly effective SERS structure with broad applications in environmental science, analytical chemistry, etc.

Serum Raman spectroscopy combined with multiple algorithms for diagnosing thyroid dysfunction and chronic renal failure

In this study, 60 samples taken from patients with thyroid dysfunction, 40 samples taken from patients with chronic renal failure (CRF) and 60 samples taken from healthy people were classified. We used partial least squares (PLS) to extract features to reduce the dimension of the spectral data to discriminate among the different samples. The Decision Trees (DT), Extreme Learning Machine (ELM), Probabilistic Neural Network (PNN), Back Propagation Neural Network (BPNN) and Learning Vector Quantization (LVQ) algorithms were used to build classification models and compare the results. The PLS-PNN algorithm distinguished between patients with thyroid dysfunction and patients with chronic renal failure with up to a 96.67 % accuracy rate, the PLS-BP algorithm distinguished between patients with chronic renal failure and healthy people with up to a 98.33 % accuracy rate, and the PLS-PNN algorithm and the PLS-DT algorithm distinguished between healthy people and patients with chronic renal failure with up to a 100 % accuracy rate. The results showed that serum Raman spectroscopy can be used in conjunction with classification algorithms to rapidly and accurately diagnose and distinguish between thyroid dysfunction and chronic renal failure.

Towards precision nanomedicine for cerebrovascular diseases with emphasis on Cerebral Cavernous Malformation (CCM)

Introduction: Cerebrovascular diseases encompass various disorders of the brain vasculature, such as ischemic/hemorrhagic strokes, aneurysms, and vascular malformations, also affecting the central nervous system leading to a large variety of transient or permanent neurological disorders. They represent major causes of mortality and long-term disability worldwide, and some of them can be inherited, including Cerebral Cavernous Malformation (CCM), an autosomal dominant cerebrovascular disease linked to mutations in CCM1/KRIT1, CCM2, or CCM3/PDCD10 genes.Areas covered: Besides marked clinical and etiological heterogeneity, some commonalities are emerging among distinct cerebrovascular diseases, including key pathogenetic roles of oxidative stress and inflammation, which are increasingly recognized as major disease hallmarks and therapeutic targets. This review provides a comprehensive overview of the different clinical features and common pathogenetic determinants of cerebrovascular diseases, highlighting major challenges, including the pressing need for new diagnostic and therapeutic strategies, and focusing on emerging innovative features and promising benefits of nanomedicine strategies for early detection and targeted treatment of such diseases.Expert opinion: Specifically, we describe and discuss the multiple physico-chemical features and unique biological advantages of nanosystems, including nanodiagnostics, nanotherapeutics, and nanotheranostics, that may help improving diagnosis and treatment of cerebrovascular diseases and neurological comorbidities, with an emphasis on CCM disease.

Two dimensional BP@AuNP nanocomposites for photothermal/photodynamic therapy mediated wound disinfection and infected wound healing under a single light source

BP@AuNP nanocomposites can perform photothermal and photodynamic therapies simultaneously and exhibited a synergistic combination of multiple therapies for S. aureus and E. coli under a 650 nm laser.

Optical biosensors: an exhaustive and comprehensive review

Optical biosensors have exhibited worthwhile performance in detecting biological systems and promoting significant advances in clinical diagnostics, drug discovery, food process control, and environmental monitoring. Without complexity in their pretreatment and probable influence on the nature of target molecules, these biosensors have additional advantages such as high sensitivity, robustness, reliability, and potential to be integrated on a single chip. In this review, the state of the art optical biosensor technologies, including those based on surface plasmon resonance (SPR), optical waveguides, optical resonators, photonic crystals, and optical fibers, are presented. The principles for each type of biosensor are concisely introduced and particular emphasis has been placed on recent achievements. The strengths and weaknesses of each type of biosensor have been outlined as well. Concluding remarks regarding the perspectives of future developments are discussed.

Photonic-Plasmonic Nanostructures for Solar Energy Utilization and Emerging Biosensors

Issues related to global energy and environment as well as health crisis are currently some of the greatest challenges faced by humanity, which compel us to develop new pollution-free and sustainable energy sources, as well as next-generation biodiagnostic solutions. Optical functional nanostructures that manipulate and confine light on a nanometer scale have recently emerged as leading candidates for a wide range of applications in solar energy conversion and biosensing. In this review, recent research progress in the development of photonic and plasmonic nanostructures for various applications in solar energy conversion, such as photovoltaics, photothermal conversion, and photocatalysis, is highlighted. Furthermore, the combination of photonic and plasmonic nanostructures for developing high-efficiency solar energy conversion systems is explored and discussed. We also discuss recent applications of photonic-plasmonic-based biosensors in the rapid management of infectious diseases at point-of-care as well as terahertz biosensing and imaging for improving global health. Finally, we discuss the current challenges and future prospects associated with the existing solar energy conversion and biosensing systems.

Applications of surface-enhanced Raman spectroscopy in detection fields

Surface-enhanced Raman spectroscopy (SERS) is a Raman spectroscopy technique that has been widely used in food safety, environmental monitoring, medical diagnosis and treatment and drug monitoring because of its high selectivity, sensitivity, rapidness, simplicity and specificity in identifying molecular structures. This review introduces the detection mechanism of SERS and summarizes the most recent progress concerning the use of SERS for the detection and characterization of molecules, providing references for the later research of SERS in detection fields.

Biosensing based on surface-enhanced Raman spectroscopy as an emerging/next-generation point-of-care approach for acute myocardial infarction diagnosis

Cardiovascular disease is a major global health issue. In particular, acute myocardial infarction (AMI) requires urgent attention and early diagnosis. The use of point-of-care diagnostics has resulted in the improved management of cardiovascular disease, but a major drawback is that the performance of POC devices does not rival that of central laboratory tests. Recently, many studies and advances have been made in the field of surface-enhanced Raman scattering (SERS), including the development of POC biosensors that utilize this detection method. Here, we present a review of the strengths and limitations of these emerging SERS-based biosensors for AMI diagnosis. The ability of SERS to multiplex sensing against existing POC detection methods are compared and discussed. Furthermore, SERS calibration-free methods that have recently been explored to minimize the inconvenience and eliminate the limitations caused by the limited linear range and interassay differences found in the calibration curves are outlined. In addition, the incorporation of artificial intelligence (AI) in SERS techniques to promote multivariate analysis and enhance diagnostic accuracy are discussed. The future prospects for SERS-based POC devices that include wearable POC SERS devices toward predictive, personalized medicine following the Fourth Industrial Revolution are proposed.

Low-Fouling Substrates for Plasmonic Sensing of Circulating Biomarkers in Biological Fluids

The monitoring of biomarkers in body fluids provides valuable prognostic information regarding disease onset and progression. Most biosensing approaches use noninvasive screening tools and are conducted in order to improve early clinical diagnosis. However, biofouling of the sensing surface may disturb the quantification of circulating biomarkers in complex biological fluids. Thus, there is a great need for antifouling interfaces to be designed in order to reduce nonspecific adsorption and prevent inactivation of biological receptors and loss of sensitivity. To address these limitations and enable their application in clinical practice, a variety of plasmonic platforms have been recently developed for biomarker analysis in easily accessible biological fluids. This review presents an overview of the latest advances in the design of antifouling strategies for the detection of clinically relevant biomarkers on the basis of the characteristics of biological samples. The impact of nanoplasmonic biosensors as point-of-care devices has been examined for a wide range of biomarkers associated with cancer, inflammatory, infectious and neurodegenerative diseases. Clinical applications in readily obtainable biofluids such as blood, saliva, urine, tears and cerebrospinal and synovial fluids, covering almost the whole range of plasmonic applications, from surface plasmon resonance (SPR) to surface-enhanced Raman scattering (SERS), are also discussed.

Label-Free Surface-Enhanced Raman Spectroscopy Biosensor for On-Site Breast Cancer Detection Using Human Tears

Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance diagnosis speed. Compared with the single infrared spectroscopy or Raman spectroscopy, the proposal can improve the detection accuracy, and can obtain more spectral features, indicating greater differences between thyroid dysfunction and normal serum samples. For discriminating different samples, principal component analysis (PCA) was first used for feature extraction to reduce the dimension of high-dimension spectral data and spectral fusion. Then, support vector machine (SVM), back propagation neural network, extreme learning machine and learning vector quantization algorithms were employed to establish the discriminant diagnostic models. The accuracy of spectral fusion of the best analytical model PCA-SVM, single Raman spectral accuracy and single infrared spectral accuracy is 83.48%, 78.26% and 80%, respectively. The accuracy of spectral fusion is higher than the accuracy of single spectrum in five classifiers. And the diagnostic accuracy of spectral fusion in the range of 2000 to 2500 cm^-1 is 81.74%, which greatly improves the sample measure speed and data analysis speed than analysis of full spectra. The results from our study demonstrate that the serum spectral fusion technique combined with multivariate statistical methods have great potential for the screening of thyroid dysfunction.

Extracellular Mitochondrial Dysfunction in Cerebrospinal Fluid of Patients with Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage

BACKGROUND

Mitochondrial dysfunction is related to brain ischemic injury and neural cell death. However, little is known about the association between mitochondrial dysfunction of cerebrospinal fluid (CSF) and delayed cerebral ischemia (DCI) following subarachnoid hemorrhage (SAH). The objective of this study was to investigate whether extracellular CSF mitochondria might serve as a potential biomarker for DCI.

METHODS

CSF samples were serially collected at 1, 3, and 5 days following SAH in 33 patients (DCI, n = 12; and non-DCI, n = 21) who underwent coil embolization. To monitor mitochondrial membrane potentials, JC-1 dye was used. The ratio (red/green) of JC-1 was considered as an indicator of intact mitochondrial membrane potential. Flow cytometry was done to analyze extracellular mitochondria particles and their possible cellular origins.

RESULTS

DCI patients had lower JC-1 red/green ratios than non-DCI patients at 1 day (3.35 [3.20-3.75] vs. 3.70 [3.40-3.95] in non-DCI) and 3 days (4.65 [4.45-5.00] vs. 5.10 [4.65-5.30] in non-DCI) after SAH. At 5 days after SAH, JC-1 red/green ratio was significantly lower in DCI than that in non-DCI (3.05 [2.90-3.35] vs. 4.20 [4.10-4.50]; p < 0.01) patients. DCI patients had a higher percentage of vWF-positive mitochondria (40.10% [38.25%-44.90%] vs. 30.20% [25.70%-36.68%]) and a lower percentage of GLAST-positive mitochondria particles (26.85% [17.10%-30.00%] vs. 31.60% [26.70%-35.00%]) than non-DCI patients. However, there was no significant difference in CD45-positive (p = 0.369) or CD41/61-positive mitochondrial particles (p = 0.155) between the two groups of patients.

CONCLUSIONS

Mitochondrial membrane potential could be a marker of DCI. JC-1 ratios seemed to be able to predict future DCI onset. Further studies are needed to determine detailed mechanisms of extracellular mitochondria-mediated cell-to-cell signals in DCI.

pH-responsive polymeric nanoparticles with tunable sizes for targeted drug delivery

Novel nanoparticles for efficient drug delivery were designed and constructed using polymeric 2,3-dialdehyde cellulose (DAC). The drug DOX was encapsulated into nanoparticles and underwent thoroughly controlled release in acidic tumor microenvironments.

Plasmonic gold nanoparticles: Optical manipulation, imaging, drug delivery and therapy

Over the past two decades, the development of plasmonic nanoparticle (NPs), especially gold (Au) NPs, is being pursued more seriously in the medical fields such as imaging, drug delivery, and theranostic systems. However, there is no comprehensive review on the effect of the physical and chemical parameters of AuNPs on their plasmonic properties as well as the use of these unique characteristic in medical activities such as imaging and therapeutics. Therefore, in this literature the surface plasmon resonance (SPR) modeling of AuNPs was accurately captured toward precision medicine. Indeed, we investigated the importance of plasmonic properties of AuNPs in optical manipulation, imaging, drug delivery, and photothermal therapy (PTT) of cancerous cells based on their physicochemical properties. Finally, some challenges regarding the commercialization of AuNPs in future medicine such as, cytotoxicity, lack of standards for medical applications, high cost, and time-consuming process were discussed.

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.

A silver-nanoparticle/cellulose-nanofiber composite as a highly effective substrate for surface-enhanced Raman spectroscopy

A highly active surface-enhanced Raman scattering (SERS) substrate was developed by facile deposition of silver nanoparticles onto cellulose fibers of ordinary laboratory filter paper. This was achieved by means of the silver mirror reaction in a manner to control both the size of the silver nanoparticles and the silver density of the substrate. This paper-based substrate is composed of a particle-on-fiber structure with the unique three-dimensional network morphology of the cellulose matrix. For such a SERS substrate with optimized size of the silver nanoparticles (ca. 70 nm) and loading density of silver (17.28 wt %), a remarkable detection limit down to the sub-attomolar (1 × 10^-16 M) level and an enhancement factor of 3 × 10⁶ were achieved by using Rhodamine 6G as the analyte. Moreover, this substrate was applied to monitor the molecular recognition through multiple hydrogen bonds in between nucleosides of adenosine and thymidine. This low-cost, highly sensitive, and biocompatible paper-based SERS substrate holds considerable potentials for the detection and analyses of chemical and biomolecular species.

Paper-Based Surface-Enhanced Raman Spectroscopy for Diagnosing Prenatal Diseases in Women

We report the development of a surface-enhanced Raman spectroscopy sensor chip by decorating gold nanoparticles (AuNPs) on ZnO nanorod (ZnO NR) arrays vertically grown on cellulose paper (C). We show that these chips can enhance the Raman signal by 1.25 × 10⁷ with an excellent reproducibility of <6%. We show that we can measure trace amounts of human amniotic fluids of patients with subclinical intra-amniotic infection (IAI) and preterm delivery (PTD) using the chip in combination with a multivariate statistics-derived machine-learning-trained bioclassification method. We can detect the presence of prenatal diseases and identify the types of diseases from amniotic fluids with >92% clinical sensitivity and specificity. Our technology has the potential to be used for the early detection of prenatal diseases and can be adapted for point-of-care applications.