Raman Spectroscopy: A Tool for Molecular Fingerprinting of Brain Cancer

Current research status of Raman spectroscopy in glioma detection

Glioma is the most common primary tumor of the nervous system. Conventional diagnostic methods for glioma often involve time-consuming or reliance on externally introduced materials. Consequently, there is an urgent need for rapid and reliable diagnostic techniques. Raman spectroscopy has emerged as a promising tool, offering rapid, accurate, and label-free analysis with high sensitivity and specificity in biomedical applications. In this review, the fundamental principles of Raman spectroscopy have been introduced, and then the progress of applying Raman spectroscopy in biomedical studies has been summarized, including the identification and typing of glioma. The challenges encountered in the clinical application of Raman spectroscopy for glioma have been discussed, and the prospects have also been envisioned.

Development of a 3D Printing-Enabled Cost-Effective Multimodal Raman Probe with High Signal-to-noise Ratio Raman Spectrum Measurements

Raman spectroscopy has emerged as a pivotal analytical instrument, valued for its nondestructive capabilities and its capacity to provide essential material-specific insights. However, the excessive costs associated with commercially available Raman instruments present a barrier to their accessibility for many academic institutions and broader usage. Herein, we introduce an affordable and accessible approach to constructing a versatile Raman instrument capable of accommodating both spectroscopic and microscopic analyses. Through this multimodal approach that concurrently captures Raman signal and image data, we demonstrate color-based alcohol detection, showcase a high signal-to-noise ratio achieved through meticulous hardware design and signal processing, and present a cost-effective, modular design utilizing 3D printing technology. This system offers adaptability to address diverse research needs and requirements. We systematically detail the fabrication process, including the utilization of a 3D printer to produce necessary components, ultimately resulting in the assembly of a functional Raman probe system. Our experiments and subsequent analyses substantiate the accuracy and reliability of the constructed system. Specifically, we conducted experiments involving three distinct samples: water, ethanol, and methanol using the Raman probe, successfully confirming their unique Raman spectra. Furthermore, our Raman probe accurately identified ethanol concentration by assessing mixed samples with varying water-to-ethanol ratios and demonstrated a coefficient of determination value of 0.9993. This underscores the performance of the constructed Raman probe and positions it as a viable option for characterization, particularly in regions where access to conventional Raman probe may be limited.

Evaluating the accuracy of Raman spectroscopy in differentiating leukemia patients from healthy individuals: A systematic review and meta-analysis

PURPOSE

To assess the accuracy of Raman spectroscopy in distinguishing between patients with leukemia and healthy individuals.

METHOD

PubMed, Embase, Web of Science, Cochrane Library, and CNKI databases were searched for relevant articles published from inception of the respective database to November 1, 2023. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), were calculated along with their corresponding 95 % confidence intervals (CI). A summary comprehensive receiver operating characteristic curve (SROC) was constructed and the area under the curve (AUC) was calculated. The degree of heterogeneity was tested and analyzed.

RESULTS

Fifteen groups of original studies from 13 articles were included. The pooled SEN and SPE were 0.93 (95 % CI, [0.92 -0.93]) and 0.91(95 % CI, [0.90-0.92]), respectively. The DOR was 613.01 (95 %CI, [270.79-1387.75]), and the AUC was 0.99. The Deeks' funnel plot asymmetry test indicated no significant publication bias among the included studies (bias coefficient, 40.80; P = 0.13 < 0.10). The meta-regression analysis findings indicated that the observed heterogeneity could be attributed to variations in sample categories and Raman spectroscopy techniques.

CONCLUSION

We confirmed that Raman spectroscopy has good accuracy in differentiating patients with leukemia from healthy individuals, and may become a means of leukemia screening in clinical practice. In the case of analysis based on live cells using surface-enhanced Raman spectroscopy (SERS) improved diagnostic efficacy was observed.

Advancements in Neurosurgical Intraoperative Histology

Despite their relatively low incidence globally, central nervous system (CNS) tumors remain amongst the most lethal cancers, with only a few other malignancies surpassing them in 5-year mortality rates. Treatment decisions for brain tumors heavily rely on histopathological analysis, particularly intraoperatively, to guide surgical interventions and optimize patient outcomes. Frozen sectioning has emerged as a vital intraoperative technique, allowing for highly accurate, rapid analysis of tissue samples, although it poses challenges regarding interpretive errors and tissue distortion. Raman histology, based on Raman spectroscopy, has shown great promise in providing label-free, molecular information for accurate intraoperative diagnosis, aiding in tumor resection and the identification of neurodegenerative disease. Techniques including Stimulated Raman Scattering (SRS), Coherent Anti-Stokes Raman Scattering (CARS), Surface-Enhanced Raman Scattering (SERS), and Tip-Enhanced Raman Scattering (TERS) have profoundly enhanced the speed and resolution of Raman imaging. Similarly, Confocal Laser Endomicroscopy (CLE) allows for real-time imaging and the rapid intraoperative histologic evaluation of specimens. While CLE is primarily utilized in gastrointestinal procedures, its application in neurosurgery is promising, particularly in the context of gliomas and meningiomas. This review focuses on discussing the immense progress in intraoperative histology within neurosurgery and provides insight into the impact of these advancements on enhancing patient outcomes.

Application of Nanohybrid Substrates with Layer-by-Layer Self-Assembling Properties to High-Sensitivity Surface-Enhanced Raman Scattering Detection

The present study was conducted to prepare and investigate large-area, high-sensitivity surface-enhanced Raman scattering (SERS) substrates. Organic/inorganic nanohybrid dispersants consisting of an amphiphilic triblock copolymer (hereafter referred to simply as "copolymer") and graphene oxide (GO) were used to stabilize the growth and size of gold nanoparticles (AuNPs). Ion-dipole forces were present between the AuNPs and copolymer dispersants, while the hydrogen bonds between GO and the copolymer prevented the aggregation of GO, thereby stabilizing the AuNP/GO nanohybrids. Transmission electron microscopy (TEM) revealed that the AuNPs had particle sizes of 25-35 nm and a relatively uniform size distribution. The AuNP/GO nanohybrids were deposited onto the glass substrate by using the solution drop-casting method and employed for SERS detection. The self-assembling properties of two-dimensional sheet-like GO led to a regular lamellar arrangement of AuNP/GO nanohybrids, which could be used for the preparation of large-area SERS substrates. Following removal of the copolymer by annealing at 300 °C for 2 h, measurements were obtained under scanning electron microscopy. The results confirmed that 2D GO nanosheets were capable of stabilizing AuNPs, with the final size reaching approximately 40 nm. These AuNPs were adsorbed on both sides of the GO nanosheets. Because the GO nanosheets were merely 5 nm-thick, a good three-dimensional hot-junction effect was generated along the z-axis of the AuNPs. Lastly, the prepared material was used for the SERS detection of rhodamine 6G (R6G), a commonly used highly fluorescent dye. An enhancement factor (EF) of up to 3.5 × 106 was achieved, and the limit of detection was approximately 10-10 M. Detection limits of 10-10 M and < 10-10 M were also observed with the detection of Direct Blue 200 and the biological molecule adenine. It is therefore evident that AuNP/copolymer/GO nanohybrids are large-area flexible SERS substrates that hold great potential in environmental monitoring and biological system detection applications.