Molecular-Sieving Label-Free Surface-Enhanced Raman Spectroscopy for Sensitive Detection of Trace Small-Molecule Biomarkers in Clinical Samples.

Small-molecule biomarkers are ubiquitous in biological fluids with pathological implications, but major challenges persist in their quantitative analysis directly in complex clinical samples. Herein, a molecular-sieving label-free surface-enhanced Raman spectroscopy (SERS) biosensor is reported for selective quantitative analysis of trace small-molecule trimetazidine (TMZ) in clinical samples. Our biosensor is fabricated by decorating a superhydrophobic monolayer of microporous metal-organic frameworks (MOF) shell-coated Au nanostar nanoparticles on a silicon substrate.

SERS surgical navigation with postsurgical immunotherapy of local microtumors and distant metastases for improved anticancer outcomes.

The standard of clinical care of most malignant solid cancers is surgery, followed by postsurgical adjuvant therapy, but microtumor lesions left behind after surgery and invisible distant metastases are the major reasons for treatment failure. Here, we report an integrated strategy combining surface-enhanced Raman spectroscopy (SERS) surgical navigation with postsurgical immunotherapy elicited by near-infrared II photothermal treatment and programmed death-1 antibody. The SERS surgical navigation is principally based on the multifunctional optical probes (namely, MATRA probes) integrating with T-weighted magnetic resonance (MR) imaging, photothermal effect and Raman spectroscopic detection.

Targeted SERS Imaging and Intraoperative Real-Time Elimination of Microscopic Tumors for Improved Breast-Conserving Surgery.

Breast-conserving surgery is the favorable option for breast cancer patients owing to its advantages of less aggressiveness and better cosmetic outcomes over mastectomy. However, it often suffers from postsurgical lethal recurrence due to the incomplete removal of microscopic tumors. Here, a surface-enhanced Raman scattering (SERS) surgical strategy is reported for precise delineation of tumor margins and intraoperative real-time elimination of microscopic tumor foci, which is capable of complete surgical removal of breast tumors and significantly improve the outcomes of breast-conserving surgery without local tumor recurrence.

Self-calibrating surface-enhanced Raman scattering-lateral flow immunoassay for determination of amyloid-β biomarker of Alzheimer's disease.

Rapid early diagnosis of Alzheimer's disease (AD) is critical for its effective and prompt treatment since the clinically available treatments can only relieve the symptoms or slow the disease progression. However, it is still a grand challenge to accurately diagnose AD at its early stage because of the indiscernible early symptoms and the lack of sensitive detection tools. Here, we develop a self-calibrating surface-enhanced Raman scattering (SERS)-lateral flow immunoassay (LFIA) biosensor for quantitative analysis of amyloid-β1-42 (Aβ1-42) biomarker in biofluids, enabling accurate AD diagnosis.

Absolute Quantification of Serum Exosomes in Patients with an SERS-Lateral Flow Strip Biosensor for Noninvasive Clinical Cancer Diagnosis.

Exosomes (exos) widely existing in body fluids show great potential for noninvasive cancer diagnosis. Quantitative analysis of exos is traditionally performed by targeting specific exosomal surface proteins, but it is often imprecise due to the common expression of exosomal proteins and subtle expression differences between different cancer subtypes. Herein, we report quantitative surface-enhanced Raman spectroscopy (SERS) of serum exos through a combination of a paper-based lateral flow strip (LFS) biosensor with multivariate spectral unmixing analysis rather than simply quantifying exosomal proteins.

Integrated SERS-Vertical Flow Biosensor Enabling Multiplexed Quantitative Profiling of Serological Exosomal Proteins in Patients for Accurate Breast Cancer Subtyping.

Protein profiles of exosomes (EXOs) in clinical samples of cancer patients have become a promising diagnostic and therapeutic biomarker. However, simultaneous quantitative analysis of multiple exosomal proteins of interest remains challenging. To address the unmet need, we develop a paper-based surface-enhanced Raman spectroscopy (SERS)-vertical flow biosensor, named iREX (integrated Raman spectroscopic EXO) biosensor, for multiplexed quantitative profiling of exosomal proteins in clinical serum samples of patients.

Quantitative Label-Free SERS Detection of Trace Fentanyl in Biofluids with a Freestanding Hydrophobic Plasmonic Paper Biosensor.

The prevalence of fentanyl abuse raises global public health concerns with an unprecedented surge in overdose deaths. Rapid identification and quantification of fentanyl in biofluids is of paramount importance to combat fentanyl abuse for law enforcement agencies and promptly treat patients for medical professionals. Herein, a freestanding surface-enhanced Raman spectroscopy (SERS) biosensor with excellent condensing enrichment capability, termed FrEnSERS biosensor, is reported for quantitative label-free detection of trace fentanyl in biofluids.

Artificial Intelligent Label-Free SERS Profiling of Serum Exosomes for Breast Cancer Diagnosis and Postoperative Assessment.

Breast cancer subtypes have important implications of treatment responses and clinical outcomes. Exosomes have been considered as promising biomarkers for liquid biopsies, but the utility of exosomes for accurate diagnosis of distinct breast cancer subtypes is a grand challenge due to the difficulty in uncovering the subtle compositional difference in complex clinical settings. Herein, we report an artificial intelligent surface-enhanced Raman spectroscopy (SERS) strategy for label-free spectroscopic analysis of serum exosomes, allowing for accurate diagnosis of breast cancer and assessment of surgical outcomes.

Label-Free Plasmon-Enhanced Spectroscopic HER2 Detection for Dynamic Therapeutic Surveillance of Breast Cancer.

The expression of human epidermal growth factor receptor-2 (HER2) has important implications for pathogenesis, progression, and therapeutic efficacy of breast cancer. The detection of its variation during the treatment is crucial for therapeutic decision-making but remains a grand challenge, especially at the cellular level. Here, we develop a machine learning-driven surface-enhanced Raman spectroscopy (SERS)-integrated strategy for label-free detection of cellular HER2.