Plasmonics-enhanced spikey nanorattle-based biosensor for direct SERS detection of mRNA cancer biomarkers.

We present a plasmonics-enhanced spikey nanorattle-based biosensor for direct surface-enhanced Raman scattering (SERS) detection of mRNA cancer biomarkers. Early detection of cancers such as head and neck squamous cell carcinoma (HNSCC) is critical for improving patient outcomes in regions with limited access to traditional diagnostic methods. Our method targets Keratin 14 (KRT14), a promising diagnostic mRNA biomarker for HNSCC, using a sandwich hybridization approach with magnetic beads and SERS spikey nanorattles (SpNR). We synthesized SpNR with a core-gap-shell structure to enhance SERS signals, achieving a limit of detection of 90 femtomolar. A pilot study using clinical samples demonstrated the efficacy of our biosensor in distinguishing between tissue with positive or negative diagnosis for HNSCC, highlighting its potential for rapid and sensitive cancer diagnostics in low-resource settings. This plasmonic assay offers a promising avenue for portable and high-specificity detection of nucleic acid biomarkers, with implications for early cancer detection and improved patient care, especially in middle and low-resource settings.

Plasmonic-Enhanced Colorimetric Lateral Flow Immunoassays Using Bimetallic Silver-Coated Gold Nanostars.

The colorimetric lateral flow immunoassay (cLFIA) has gained widespread attention as a point-of-care testing (POCT) technique due to its low cost, short analysis time, portability, and capability of being performed by unskilled operators with minimal requirement of reagents. However, the low analytical sensitivity of conventional LFIA based on colloidal gold nanospheres limits their applications for sensitive detection of trace amounts of target analytes. In this study, we introduced a novel plasmonic-enhanced colorimetric LFIA (PE-cLFIA) platform featuring bimetallic silver-coated gold nanostars (BGNS) with exceptional optical properties, leading to ultrahigh visual color brightness. The BGNS-based PE-cLFIA was successfully applied to detect a model analyte, low-calcium response V (LcrV), a virulence protein factor found in Yersinia pestis, the causative agent of bubonic plague. The PE-cLFIA sensing using BGNS-3 composed of 45 nm silver thickness showed a high visual colorimetric sensitivity with a detection limit as low as 13.7 pg/mL, which was around 50 times more sensitive than that of a traditional gold nanoparticle-based LFIA. In addition, the antibody-conjugated BGNS-3 showed excellent stability over 6 months. To illustrate the potential for clinical applications, we demonstrated that our LFIA platform for detecting LcrV spiked in human serum without any sample preprocessing exhibited a detection limit of 22.8 pg/mL. These results open up new opportunities for developing hybrid nanoparticle systems for sensitive POCT PE-cLFIA screening for infectious disease detection.

A Simple and Sensitive Wearable SERS Sensor Utilizing Plasmonic-Active Gold Nanostars.

Wearable sweat sensors hold great potential for offering detailed health insights by monitoring various biomarkers present in sweat, such as glucose, lactate, uric acid, and urea, in real time. However, most previously reported sensors, primarily based on electrochemical technology, are limited to monitoring only a single analyte at a given time. This study introduces a simple, sensitive, wearable patch based on surface-enhanced Raman spectroscopy (SERS), integrated with highly plasmonically active sharp-branched gold nanostars (GNS) for the simultaneous detection of three sweat biomarkers: lactate, urea, and glucose. We have fabricated the GNS on commercially available adhesive tape, resulting in achieving a low-cost, flexible, and adhesive wearable SERS patch. The limits of detection for lactate, urea, and glucose were achieved at 0.7, 0.6, and 0.7 µM, respectively, which are significantly lower than the clinically relevant concentrations of these biomarkers in sweat. We further evaluated the performance of our wearable SERS patch during outdoor activities, including sitting, walking, and running. To evaluate its overall effectiveness, we simultaneously measured the concentrations of lactate, urea, and glucose during these activities. Overall, our simple, sensitive wearable SERS sensor represents a significant breakthrough by enabling the simultaneous detection of lactate, urea, and glucose present in sweat, marking a major step toward future applications in autonomous and noninvasive personalized healthcare monitoring at home.

Improved solution-based SERS detection of creatinine by inducing hydrogen-bonding interaction for effective analyte capture.

Recently, solution-based surface-enhanced Raman scattering (SERS) detection technique has been widely recognized due to its cost-effectiveness, simplicity, and ease of use. However, solution-based SERS is limited for practical applications mainly because of the weak adsorption affinity of the target biomolecules to the surface of plasmonic nanoparticles. Herein, we developed a highly sensitive solution-based SERS sensing platform based on mercaptopropionic acid (MPA)-capped silver-coated gold nanostars (SGNS@MPA), which allows efficient enrichment on the nanostars surface for improved detection of an analyte: creatinine, a potential biomarker of chronic kidney disease (CKD). The SGNS@MPA exhibited high enrichment ability towards creatinine molecules in alkaline medium (pH-9) through multiple hydrogen bonding interaction, which causes aggregation of the nanoparticles and enhances the SERS signal of creatinine. The detection limit for creatinine was achieved at 0.1 nM, with a limit of detection (LOD) value of 14.6 pM. As a proof-of-concept demonstration, we conducted the first quantitative detection of creatinine in noninvasive human fluids, such as saliva and sweat, under separation-free conditions. We achieved a detection limit of up to 1 nM for both saliva and sweat, with LOD values as low as 0.136 nM for saliva and 0.266 nM for sweat. Overall, our molecular enrichment strategy offers a new way to improve the solution-based SERS detection technique for real-world practical applications in point-of-care settings and low-resource settings.

Plasmonics nanorod biosensor for in situ intracellular detection of gene expression biomarkers in intact plant systems.

The intracellular developmental processes in plants, particularly concerning lignin polymer formation and biomass production are regulated by microRNAs (miRNAs). MiRNAs including miR397b are important for developing efficient and cost-effective biofuels. However, traditional methods of monitoring miRNA expression, like PCR, are time-consuming, require sample extraction, and lack spatial and temporal resolution, especially in real-world conditions. We present a novel approach using plasmonics nanosensing to monitor miRNA activity within living plant cells without sample extraction. Plasmonic biosensors using surface-enhanced Raman scattering (SERS) detection offer high sensitivity and precise molecular information. We used the Inverse Molecular Sentinel (iMS) biosensor on unique silver-coated gold nanorods (AuNR@Ag) with a high-aspect ratio to penetrate plant cell walls for detecting miR397b within intact living plant cells. MiR397b overexpression has shown promise in reducing lignin content. Thus, monitoring miR397b is essential for cost-effective biofuel generation. This study demonstrates the infiltration of nanorod iMS biosensors and detection of non-native miRNA 397b within plant cells for the first time. The investigation successfully demonstrates the localization of nanorod iMS biosensors through TEM and XRF-based elemental mapping for miRNA detection within plant cells of Nicotiana benthamiana. The study integrates shifted-excitation Raman difference spectroscopy (SERDS) to decrease background interference and enhance target signal extraction. In vivo SERDS testing confirms the dynamic detection of miR397b in Arabidopsis thaliana leaves after infiltration with iMS nanorods and miR397b target. This proof-of-concept study is an important stepping stone towards spatially resolved, intracellular miRNA mapping to monitor biomarkers and biological pathways for developing efficient renewable biofuel sources.

Osmosensor-mediated control of Ca2+ spiking in pollen germination.

Higher plants survive terrestrial water deficiency and fluctuation by arresting cellular activities (dehydration) and resuscitating processes (rehydration). However, how plants monitor water availability during rehydration is unknown. Although increases in hypo-osmolarity-induced cytosolic Ca2+ concentration (HOSCA) have long been postulated to be the mechanism for sensing hypo-osmolarity in rehydration1,2, the molecular basis remains unknown. Because osmolarity triggers membrane tension and the osmosensing specificity of osmosensing channels can only be determined in vivo3-5, these channels have been classified as a subtype of mechanosensors. Here we identify bona fide cell surface hypo-osmosensors in Arabidopsis and find that pollen Ca2+ spiking is controlled directly by water through these hypo-osmosensors-that is, Ca2+ spiking is the second messenger for water status. We developed a functional expression screen in Escherichia coli for hypo-osmosensitive channels and identified OSCA2.1, a member of the hyperosmolarity-gated calcium-permeable channel (OSCA) family of proteins6. We screened single and high-order OSCA mutants, and observed that the osca2.1/osca2.2 double-knockout mutant was impaired in pollen germination and HOSCA. OSCA2.1 and OSCA2.2 function as hypo-osmosensitive Ca2+-permeable channels in planta and in HEK293 cells. Decreasing osmolarity of the medium enhanced pollen Ca2+ oscillations, which were mediated by OSCA2.1 and OSCA2.2 and required for germination. OSCA2.1 and OSCA2.2 convert extracellular water status into Ca2+ spiking in pollen and may serve as essential hypo-osmosensors for tracking rehydration in plants.

Caged gold nanostars: a novel plasmonic nanoplatform with potential theranostic applications.

Here, we first introduce caged gold nanostars (C-GNS), a novel hybrid nanoplatform combining the exceptional plasmonic properties of nanostars with the loading capability of hollow-shell structures. We present two synthetic routes used to produce C-GNS particles and highlight the benefits of the galvanic replacement-free approach. FEM simulations explore the enhanced plasmonic properties of this novel nanoparticle morphology. Finally, in a proof-of-concept study, we successfully demonstrate in vivo hyperspectral imaging and photothermal treatment of tumors in a mouse model with the C-GNS nanoplatform.

Dual-Modal Colorimetric and Surface-Enhanced Raman Scattering (SERS)-Based Lateral Flow Immunoassay for Ultrasensitive Detection of SARS-CoV-2 Using a Plasmonic Gold Nanocrown.

The 2019 coronavirus disease (COVID-19) outbreak created an unprecedented need for rapid, sensitive, and cost-effective point-of-care diagnostic tests to prevent and mitigate the spread of the SARS-CoV-2 virus. Herein, we demonstrated an advanced lateral flow immunoassay (LFIA) platform with dual-functional [colorimetric and surface-enhanced Raman scattering (SERS)] detection of the spike 1 (S1) protein of SARS-CoV-2. The nanosensor was integrated with a specially designed core-gap-shell morphology consisting of a gold shell decorated with external nanospheres, a structure referred to as gold nanocrown (GNC), labeled with a Raman reporter molecule 1,3,3,1',3',3'-hexamethyl-2,2'-indotricarbocyanine iodide (HITC) to produce a strong colorimetric signal as well as an enhanced SERS signal. Among the different plasmonics-active GNC nanostructures, the GNC-2 morphology, which has a shell decorated with an optimum number and size of nanospheres, produces an intense dark-blue colorimetric signal and ultrahigh SERS signal. The limit of detection (LOD) of the S1 protein via colorimetric detection LFIA was determined to be 91.24 pg/mL. On the other hand, the LOD for the SERS LFIA method was more than three orders of magnitude lower at 57.21 fg/mL. Furthermore, we analyzed the performance of the GNC-2 nanosensor for directly analyzing the S1 protein spiked in saliva samples without any sample pretreatment and achieving the LOD as low as 39.65 fg/mL using SERS-based plasmonics-enhanced LFIA, indicating ultrahigh detection sensitivity. Overall, our GNC nanosensor showed excellent sensitivity, reproducibility, and rapid detection of the SARS-CoV-2 S1 protein, demonstrating excellent potential as a promising point-of-care platform for the early detection of respiratory virus infections.

Acoustic separation and concentration of exosomes for nucleotide detection: ASCENDx.

Efficient isolation and analysis of exosomal biomarkers hold transformative potential in biomedical applications. However, current methods are prone to contamination and require costly consumables, expensive equipment, and skilled personnel. Here, we introduce an innovative spaceship-like disc that allows Acoustic Separation and Concentration of Exosomes and Nucleotide Detection: ASCENDx. We created ASCENDx to use acoustically driven disc rotation on a spinning droplet to generate swift separation and concentration of exosomes from patient plasma samples. Integrated plasmonic nanostars on the ASCENDx disc enable label-free detection of enriched exosomes via surface-enhanced Raman scattering. Direct detection of circulating exosomal microRNA biomarkers from patient plasma samples by the ASCENDx platform facilitated a diagnostic assay for colorectal cancer with 95.8% sensitivity and 100% specificity. ASCENDx overcomes existing limitations in exosome-based molecular diagnostics and holds a powerful position for future biomedical research, precision medicine, and point-of-care medical diagnostics.

A simple low-cost flexible plasmonic patch based on spiky gold nanostars for ultra-sensitive SERS sensing.

Recently, transparent and flexible surface-enhanced Raman scattering (SERS) substrates have received great interest for direct point-of-care detection of analytes on irregular nonplanar surfaces. In this study, we proposed a simple cost-effective strategy to develop a flexible SERS patch utilizing multibranched sharp spiked gold nanostars (GNS) decorated on a commercially available adhesive Scotch Tape for achieving ultra-high SERS sensitivity. The experimental SERS measurements were correlated with theoretical finite element modeling (FEM), which indicates that the GNS having a 2.5 nm branch tip diameter (GNS-4) exhibits the strongest SERS enhancement. Using rhodamine 6G (R6G) as a model analyte, the SERS performance of the flexible SERS patch exhibited a minimum detection limit of R6G as low as 1 pM. The enhancement factor of the SERS patch with GNS-4 was calculated as 6.2 × 108, which indicates that our flexible SERS substrate has the potential to achieve ultra-high sensitivity. The reproducibility was tested with 30 different spots showing a relative standard deviation (RSD) of SERS intensity of about 5.4%, indicating good reproducibility of the SERS platform. To illustrate the usefulness of the flexible SERS sensor patch, we investigated the detection of a carcinogenic compound crystal violet (CV) on fish scales, which is often used as an effective antifungal agent in the aquaculture industry. The results realized the trace detection of CV with the minimum detection limit as low as 1 pM. We believe that our transparent, and flexible SERS patch based on GNS-4 has potential as a versatile, low-cost platform for real-world SERS sensing applications on nonplanar surfaces.

Rapid SERS assay for determination of the opioid fentanyl using silver-coated sharply branched gold nanostars.

A high-throughput surface-enhanced Raman scattering (SERS)-sensing platform is presented for FNT detection in human urine without any sample preparation. The sensing platform is based on plasmonics-active silver-coated sharply branched gold nanostars (SGNS). The effect of silver thickness was investigated experimentally and theoretically, and the results indicated that SERS enhancement was maximum at an optimum silver thickness of 45 nm on the sharply spiked SGNS. The proposed high-throughput SERS platform exhibited ultrahigh sensitivity and excellent enhancement uniformity for a model analyte, i.e., crystal violet. Moreover, the SERS-sensing platform demonstrated good sensitivity of FNT spiked in human urine samples with two differential linear response ranges of 2 to 0.2 µg/mL and 0.1 µg/mL to 100 pg/mL, respectively,  with a detection limit as low as 10.02 pg/mL. The spiked human urine samples show satisfactory recovery values from 92.5 to 102% with relative standard deviations (RSD) of less than 10%. In summary, the high-throughput performance of the proposed microplate-based SERS platform demonstrated great potential for rapid low-cost SERS-based sensing applications.

Surface-Enhanced Raman Spectroscopy-Based Detection of Micro-RNA Biomarkers for Biomedical Diagnosis Using a Comparative Study of Interpretable Machine Learning Algorithms.

Surface-enhanced Raman spectroscopy (SERS) has wide diagnostic applications due to narrow spectral features that allow multiplex analysis. We have previously developed a multiplexed, SERS-based nanosensor for micro-RNA (miRNA) detection called the inverse molecular sentinel (iMS). Machine learning (ML) algorithms have been increasingly adopted for spectral analysis due to their ability to discover underlying patterns and relationships within large and complex data sets. However, the high dimensionality of SERS data poses a challenge for traditional ML techniques, which can be prone to overfitting and poor generalization. Non-negative matrix factorization (NMF) reduces the dimensionality of SERS data while preserving information content. In this paper, we compared the performance of ML methods including convolutional neural network (CNN), support vector regression, and extreme gradient boosting combined with and without NMF for spectral unmixing of four-way multiplexed SERS spectra from iMS assays used for miRNA detection. CNN achieved high accuracy in spectral unmixing. Incorporating NMF before CNN drastically decreased memory and training demands without sacrificing model performance on SERS spectral unmixing. Additionally, models were interpreted using gradient class activation maps and partial dependency plots to understand predictions. These models were used to analyze clinical SERS data from single-plexed iMS in RNA extracted from 17 endoscopic tissue biopsies. CNN and CNN-NMF, trained on multiplexed data, performed most accurately with RMSElabel = 0.101 and 9.68 × 10-2, respectively. We demonstrated that CNN-based ML shows great promise in spectral unmixing of multiplexed SERS spectra, and the effect of dimensionality reduction on performance and training speed.

On the Importance of Low-Frequency Signals in Functional and Molecular Photoacoustic Computed Tomography.

In photoacoustic computed tomography (PACT) with short-pulsed laser excitation, wideband acoustic signals are generated in biological tissues with frequencies related to the effective shapes and sizes of the optically absorbing targets. Low-frequency photoacoustic signal components correspond to slowly varying spatial features and are often omitted during imaging due to the limited detection bandwidth of the ultrasound transducer, or during image reconstruction as undesired background that degrades image contrast. Here we demonstrate that low-frequency photoacoustic signals, in fact, contain functional and molecular information, and can be used to enhance structural visibility, improve quantitative accuracy, and reduce spare-sampling artifacts. We provide an in-depth theoretical analysis of low-frequency signals in PACT, and experimentally evaluate their impact on several representative PACT applications, such as mapping temperature in photothermal treatment, measuring blood oxygenation in a hypoxia challenge, and detecting photoswitchable molecular probes in deep organs. Our results strongly suggest that low-frequency signals are important for functional and molecular PACT.

Multiplex SERS detection of polycyclic aromatic hydrocarbon (PAH) pollutants in water samples using gold nanostars and machine learning analysis.

Polycyclic aromatic hydrocarbons (PAHs) have attracted a lot of environmental concern because of their carcinogenic and mutagenic properties, and the fact they can easily contaminate natural resources such as drinking water and river water. This study presents a simple and sensitive point-of-care SERS detection of PAHs combined with machine learning algorithms to predict the PAH content more precisely and accurately in real-life samples such as drinking water and river water. We first synthesized multibranched sharp-spiked surfactant-free gold nanostars (GNSs) that can generate strong surface-enhanced Raman scattering (SERS) signals, which were further coated with cetyltrimethylammonium bromide (CTAB) for long-term stability of the GNSs as well as to trap PAHs. We utilized CTAB-capped GNSs for solution-based 'mix and detect' SERS sensing of various PAHs including pyrene (PY), nitro-pyrene (NP), anthracene (ANT), benzo[a]pyrene (BAP), and triphenylene (TP) spiked in drinking water and river water using a portable Raman module. Very low limits of detection (LOD) were achieved in the nanomolar range for the PAHs investigated. More importantly, the detected SERS signal was reproducible for over 90 days after synthesis. Furthermore, we analyzed the SERS data using artificial intelligence (AI) with machine learning algorithms based on the convolutional neural network (CNN) model in order to discriminate the PAHs in samples more precisely and accurately. Using a CNN classification model, we achieved a high prediction accuracy of 90% in the nanomolar detection range and an f1 score (harmonic mean of precision and recall) of 94%, and using a CNN regression model, achieved an RMSEconc = 1.07 × 10-1 µM. Overall, our SERS platform can be effectively and efficiently used for the accurate detection of PAHs in real-life samples, thus opening up a new, sensitive, selective, and practical approach for point-of-need SERS diagnosis of small molecules in complex practical environments.

Cascade Amplified Plasmonics Molecular Biosensor for Sensitive Detection of Disease Biomarkers.

Recent advances in molecular technologies have provided various assay strategies for monitoring biomarkers, such as miRNAs for early detection of various diseases and cancers. However, there is still an urgent unmet need to develop practical and accurate miRNA analytical tools that could facilitate the incorporation of miRNA biomarkers into clinical practice and management. In this study, we demonstrate the feasibility of using a cascade amplification method, referred to as the "Cascade Amplification by Recycling Trigger Probe" (CARTP) strategy, to improve the detection sensitivity of the inverse Molecular Sentinel (iMS) nanobiosensor. The iMS nanobiosensor developed in our laboratory is a unique homogeneous multiplex bioassay technique based on surface-enhanced Raman scattering (SERS) detection, and was used to successfully detect miRNAs from clinical samples. The CARTP strategy based on the toehold-mediated strand displacement reaction is triggered by a linear DNA strand, called the "Recycling Trigger Probe" (RTP) strand, to amplify the iMS SERS signal. Herein, by using the CARTP strategy, we show a significantly improved detection sensitivity with the limit of detection (LOD) of 45 fM, which is 100-fold more sensitive than the non-amplified iMS assay used in our previous report. We envision that the further development and optimization of this strategy ultimately will allow multiplexed detection of miRNA biomarkers with ultra-high sensitivity for clinical translation and application.

On the importance of low-frequency signals in functional and molecular photoacoustic computed tomography.

In photoacoustic computed tomography (PACT) with short-pulsed laser excitation, wideband acoustic signals are generated in biological tissues with frequencies related to the effective shapes and sizes of the optically absorbing targets. Low-frequency photoacoustic signal components correspond to slowly varying spatial features and are often omitted during imaging due to the limited detection bandwidth of the ultrasound transducer, or during image reconstruction as undesired background that degrades image contrast. Here we demonstrate that low-frequency photoacoustic signals, in fact, contain functional and molecular information, and can be used to enhance structural visibility, improve quantitative accuracy, and reduce spare-sampling artifacts. We provide an in-depth theoretical analysis of low-frequency signals in PACT, and experimentally evaluate their impact on several representative PACT applications, such as mapping temperature in photothermal treatment, measuring blood oxygenation in a hypoxia challenge, and detecting photoswitchable molecular probes in deep organs. Our results strongly suggest that low-frequency signals are important for functional and molecular PACT.

Gold Nanostars Obviate Limitations to Laser Interstitial Thermal Therapy (LITT) for the Treatment of Intracranial Tumors.

PURPOSE: Laser interstitial thermal therapy (LITT) is an effective minimally invasive treatment option for intracranial tumors. Our group produced plasmonics-active gold nanostars (GNS) designed to preferentially accumulate within intracranial tumors and amplify the ablative capacity of LITT. EXPERIMENTAL DESIGN: The impact of GNS on LITT coverage capacity was tested in ex vivo models using clinical LITT equipment and agarose gel-based phantoms of control and GNS-infused central "tumors." In vivo accumulation of GNS and amplification of ablation were tested in murine intracranial and extracranial tumor models followed by intravenous GNS injection, PET/CT, two-photon photoluminescence, inductively coupled plasma mass spectrometry (ICP-MS), histopathology, and laser ablation. RESULTS: Monte Carlo simulations demonstrated the potential of GNS to accelerate and specify thermal distributions. In ex vivo cuboid tumor phantoms, the GNS-infused phantom heated 5.5× faster than the control. In a split-cylinder tumor phantom, the GNS-infused border heated 2× faster and the surrounding area was exposed to 30% lower temperatures, with margin conformation observed in a model of irregular GNS distribution. In vivo, GNS preferentially accumulated within intracranial tumors on PET/CT, two-photon photoluminescence, and ICP-MS at 24 and 72 hours and significantly expedited and increased the maximal temperature achieved in laser ablation compared with control. CONCLUSIONS: Our results provide evidence for use of GNS to improve the efficiency and potentially safety of LITT. The in vivo data support selective accumulation within intracranial tumors and amplification of laser ablation, and the GNS-infused phantom experiments demonstrate increased rates of heating, heat contouring to tumor borders, and decreased heating of surrounding regions representing normal structures.

Xenorecognition and costimulation of porcine endothelium-derived extracellular vesicles in initiating human porcine-specific T cell immune responses.

Porcine vascular endothelial cells (PECs) form a mechanistic centerpiece of xenograft rejection. Here, we determined that resting PECs release swine leukocyte antigen class I (SLA-I) but not swine leukocyte antigen class-II DR (SLA-DR) expressing extracellular vesicles (EVs) and investigated whether these EVs proficiently initiate xenoreactive T cell responses via direct xenorecognition and costimulation. Human T cells acquired SLA-I+ EVs with or without direct contact to PECs, and these EVs colocalized with T cell receptors. Although interferon gamma-activated PECs released SLA-DR+ EVs, the binding of SLA-DR+ EVs to T cells was sparse. Human T cells demonstrated low levels of proliferation without direct contact to PECs, but marked T cell proliferation was induced following exposure to EVs. EV-induced proliferation proceeded independent of monocytes/macrophages, suggesting that EVs delivered both a T cell receptor signal and costimulation. Costimulation blockade targeting B7, CD40L, or CD11a significantly reduced T cell proliferation to PEC-derived EVs. These findings indicate that endothelial-derived EVs can directly initiate T cell-mediated immune responses, and suggest that inhibiting the release of SLA-I EVs from organ xenografts has the potential to modify the xenograft rejection. We propose a secondary-direct pathway for T cell activation via xenoantigen recognition/costimulation by endothelial-derived EVs.

Ultra-trace SERS detection of cocaine and heroin using bimetallic gold-silver nanostars (BGNS-Ag).

A rapid, in-field, and reliable method for the detection of illegal drugs of abuse in biological fluids without any sample pretreatment would potentially be helpful for law enforcement, drug control officials, and public healthcare. In this study, we presented a cost-effective and highly reproducible solution-based surface-enhanced Raman scattering (SERS) platform utilizing a portable Raman instrument for fast sensitive SERS detection of illegal drugs, such as cocaine, and heroin in human urine without any sample preprocessing. The SERS platform was constructed for the first time by combining the superior SERS enhancement properties of bimetallic silver-coated gold nanostars (BGNS-Ag) and the advantages of suitable alkaline metal salts such as NaI for SERS signal amplification. The effects of the silver thickness of BGNS-Ag and alkaline salts on the SERS performance were investigated in detail; we observed that the maximum SERS enhancement was obtained for BGNS-Ag with the maximum silver thickness (54 ± 5 nm) in presence of NaI salt. Our SERS platform shows ultra-high sensitivity of cocaine and heroin with a limit of detection (LOD) as low as 10 pg/mL for cocaine and 100 pg/mL for heroin, which was 100 times lower than that of the traditional silver nanoparticle-based illegal drug detection. As a demonstration, the platform was further applied to detect cocaine and heroin spiked in human urine without any sample preprocessing achieving a LOD of 100 pg/mL for cocaine and 1 ng/mL for heroin. Overall, our SERS detection platform shows potential for rapid, onsite, ultra-low-cost portable applications for trace detection of illegal drugs and biomarkers.