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.

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.

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.

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.

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.

miRNA probe integrated biosensor platform using bimetallic nanostars for amplification-free multiplexed detection of circulating colorectal cancer biomarkers in clinical samples.

There is a critical need for sensitive and rapid detection technologies utilizing molecular biotargets such as microRNAs (miRNAs), which regulate gene expression and are a promising class of diagnostic biomarkers for disease detection. Here, we present the development and fabrication of a highly reproducible and robust plasmonic bimetallic nanostar biosensing platform to detect miRNA targets using surfaced-enhanced Raman scattering (SERS)-based gene probes called the inverse Molecular Sentinel (iMS). We investigated and optimized the integration of iMS gene probes onto this SERS substrate, achieving ultra-sensitive detection with limits of detection of 6.8 and 16.7 zmol within the sensing region for two miRNA sequences of interest. Finally, we demonstrated the biomedical usefulness of this nanobiosensor platform with the multiplexed detection of upregulated miRNA targets, miR21 and miR221, from colorectal cancer patient plasma. The resulting SERS data are in excellent agreement with PCR data obtained from patient samples and can distinguish between healthy and cancerous patient samples. These results underline the potential of the iMS-integrated substrate nanobiosensing platform for rapid and sensitive diagnostics of cancer biomarkers for point-of-care applications.