Intelligent SERS Navigation System Guiding Brain Tumor Surgery by Intraoperatively Delineating the Metabolic Acidosis

Real-time monitoring of single dendritic cell maturation using deep learning-assisted surface-enhanced Raman spectroscopy

Background: Dynamic real-time detection of dendritic cell (DC) maturation is pivotal for accurately predicting immune system activation, assessing vaccine efficacy, and determining the effectiveness of immunotherapy. The heterogeneity of cells underscores the significance of assessing the maturation status of each individual cell, while achieving real-time monitoring of DC maturation at the single-cell level poses significant challenges. Surface-enhanced Raman spectroscopy (SERS) holds great potential for providing specific fingerprinting information of DCs to detect biochemical alterations and evaluate their maturation status. Methods: We developed Au@CpG@PEG nanoparticle as a self-reporting nanovaccine for DC activation and maturation state assessment, utilizing a label-free SERS strategy. Fingerprint vibrational spectra of the biological components in different states of DCs were collected and analyzed using deep learning Convolutional Neural Networks (CNN) algorithms, aiding in the rapid and efficient identification of DC maturation. Results: This approach enables dynamic real-time detection of DC maturation, maintaining accuracy levels above 98.92%. Conclusion: By employing molecular profiling, we revealed that the signal ratio of tryptophan-to-carbohydrate holds potential as a prospective marker for distinguishing the maturation status of DCs.

Targeted blood-brain barrier penetration and precise imaging of infiltrative glioblastoma margins using hybrid cell membrane-coated ICG liposomes

Surgical resection remains the primary treatment modality for glioblastoma (GBM); however, the infiltrative nature of GBM margins complicates achieving complete tumor removal. Additionally, the blood-brain barrier (BBB) poses a formidable challenge to effective probe delivery, thereby hindering precise imaging-guided surgery. Here, we introduce hybrid cell membrane-coated indocyanine green (ICG) liposomes (HM-Lipo-ICG) as biomimetic near-infrared (NIR) fluorescent probes for targeted BBB penetration and accurate delineation of infiltrative GBM margins. HM-Lipo-ICG encapsulates clinically approved ICG within its core and utilizes a hybrid cell membrane exterior, enabling specific targeting and enhanced BBB permeation. Quantitative assessments demonstrate that HM-Lipo-ICG achieves BBB penetration efficiency 2.8 times higher than conventional ICG liposomes. Mechanistically, CD44 receptor-mediated endocytosis facilitates BBB translocation of HM-Lipo-ICG. Furthermore, HM-Lipo-ICG enables high-contrast NIR imaging, achieving a signal-to-background ratio of 6.5 in GBM regions of an orthotopic glioma mouse model, thereby improving tumor margin detection accuracy fourfold (84.4% vs. 22.7%) compared to conventional ICG liposomes. Application of HM-Lipo-ICG facilitates fluorescence-guided precision surgery, resulting in complete resection of GBM cells. This study underscores the potential of hybrid cell membrane-coated liposomal probes in precisely visualizing and treating infiltrative GBM margins.

pH Mapping of Gliomas Using Quantitative Chemical Exchange Saturation Transfer MRI: Quasi-Steady-State, Spillover-, and MT-Corrected Omega Plot Analysis

BACKGROUND

Quantitative in-situ pH mapping of gliomas is important for therapeutic interventions, given its significant association with tumor progression, invasion, and metastasis. Although chemical exchange saturation transfer (CEST) offers a noninvasive way for pH imaging based on the pH-dependent exchange rate (ksw), the reliable quantification of ksw in glioma remains constrained due to technical challenges.

PURPOSE

To quantify the pH of gliomas by measuring the proton exchange rate through optimized omega plot analysis.

STUDY TYPE

Prospective.

PHANTOMS/ANIMAL MODEL/SUBJECTS

Creatine and murine brain lysates phantoms, six rats with glioma xenograft model, and three patients with World Health Organization grade 2-4 gliomas.

FIELD STRENGTH/SEQUENCE

11.7 T, 7.0 T, CEST imaging, T2-weighted (T2W) imaging, and T1-mapping.

ASSESSMENT

Omega plot analysis, quasi-steady-state (QUASS) analysis, multi-pool Lorentzian fitting, amine and amide concentration-independent detection, pH enhanced method with the combination of amide and guanidyl (pHenh), and magnetization transfer ratio (MTR) were utilized for pH metric quantification. The clinical outcomes were determined through radiologic follow-up and histopathological analysis.

STATISTICAL TESTS

Mann-Whitney U test was performed to compare glioma with normal tissue, and Pearson's correlation analysis was used to assess the relationship between ksw and other parameters.

RESULTS

In vitro experiments reveal that the determined ksw at 2 ppm increases exponentially with pH (creatine phantoms: ksw = 106 + 0.147 × 10(pH-4.198); lysates: ksw = 185.1 + 0.101 × 10(pH-3.914)). Omega plot analysis exhibits a linear correlation between 1/MTRRex and 1/ω1 2 in the glioma xenografts (R2 > 0.98) and glioma patients (R2 > 0.99). The exchange rate in the rat glioma decreases compared to the contralateral normal tissue (349.46 ± 30.40 s-1 vs. 403.54 ± 51.01 s-1, P = 0.025), while keeping independence from changes in concentration (r = 0.5037, P = 0.095). Similar pattern was observed in human data.

DATA CONCLUSION

Utilizing QUASS-based, spillover-, and MT-corrected omega plot analysis for the measurement of exchange rates, offers a feasible method for quantifying pH within glioma.

LEVEL OF EVIDENCE

NA TECHNICAL EFFICACY: Stage 1.

Intraoperative glioblastoma surgery-current challenges and clinical trials: An update

Surgical excision is an important part of the multimodal therapy strategy for patients with glioblastoma, a very aggressive and invasive brain tumor. While major advances in surgical methods and technology have been accomplished, numerous hurdles remain in the field of glioblastoma surgery. The purpose of this literature review is to offer a thorough overview of the current challenges in glioblastoma surgery. We reviewed the difficulties associated with tumor identification and visualization, resection extent, neurological function preservation, tumor margin evaluation, and inclusion of sophisticated imaging and navigation technology. Understanding and resolving these challenges is critical in order to improve surgical results and, ultimately, patient survival.

Precise Identification of Glioblastoma Micro-Infiltration at Cellular Resolution by Raman Spectroscopy

Precise identification of glioblastoma (GBM) microinfiltration, which is essential for achieving complete resection, remains an enormous challenge in clinical practice. Here, the study demonstrates that Raman spectroscopy effectively identifies GBM microinfiltration with cellular resolution in clinical specimens. The spectral differences between infiltrative lesions and normal brain tissues are attributed to phospholipids, nucleic acids, amino acids, and unsaturated fatty acids. These biochemical metabolites identified by Raman spectroscopy are further confirmed by spatial metabolomics. Based on differential spectra, Raman imaging resolves important morphological information relevant to GBM lesions in a label-free manner. The area under the receiver operating characteristic curve (AUC) for Raman spectroscopy combined with machine learning in detecting infiltrative lesions exceeds 95%. Most importantly, the cancer cell threshold identified by Raman spectroscopy is as low as 3 human GBM cells per 0.01 mm2. Raman spectroscopy enables the detection of previously undetectable diffusely infiltrative cancer cells, which holds potential value in guiding complete tumor resection in GBM patients.

Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience

Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.

Self-Referenced Au Nanoparticles-Coated Glass Wafers for In Situ SERS Monitoring of Cell Secretion

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for discrimination of bimolecules in complex systems. However, its practical applications face challenges such as complicated manufacturing procedures and limited scalability of SERS substrates, as well as poor reproducibility during detection which compromises the reliability of SERS-based analysis. In this study, we developed a convenient method for simultaneous fabrication of massive SERS substrates with an internal standard to eliminate the substrate-to-substrate differences. We first synthesized Au@CN@Au nanoparticles (NPs) which contain embedded internal standard molecules with a single characteristic peak in the Raman-silent region, and then deposited the NPs on 6 mm glass wafers in a 96-well plate simply by centrifugation for 3 min. The one-time obtained 96 SERS substrates have excellent intrasubstrate uniformity and intersubstrate repeatability for SERS detection by using the internal standard (relative standard deviation = 10.47%), and were able to detect both charged and neutral molecules (crystal violet and triphenylphosphine) at a concentration of 10-9 M. Importantly, cells can be directly cultured on glass wafers in the 96-well plate, enabling real time monitoring of the secretes and metabolism change in response to external stimulation. We found that the release of nucleic acids, amino acids and lipids by MDA-MB-231 cells significantly increased under hypoxic conditions. Overall, our approach enables fast and large-scale production of Au@CN@Au NPs-coated glass wafers as SERS substrates, which are homogeneous and highly sensitive for monitoring trace changes of biomolecules.

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. The technique is chiefly based on the human epidermal growth factor receptor 2 (HER2)-targeting SERS probes with integrated multifunctionalities of ultrahigh sensitive detection, significant HER2 expression suppression, cell proliferation inhibition, and superior photothermal ablation. In a HER2+ breast tumor mouse model, the remarkable capability of the SERS surgical strategy for complete removal of HER2+ breast tumors through SERS-guided surgical resection and intraoperative real-time photothermal elimination is demonstrated. The results show complete eradiation of HER2+ breast tumors without local recurrence, consequently delivering a 100% tumor-free survival. Expectedly, this SERS surgical strategy holds great promise for clinical treatment of HER2+ breast cancer with improved patients' survival.

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.

TriFNet: A triple-branch feature fusion network for pH determination by surface-enhanced Raman spectroscopy

Due to the acidic tumor microenvironment caused by metabolic changes in tumor cells, the accurate pH detection of extracellular fluid is helpful for doctors in precise tumor resection. The combination of Raman spectroscopy and deep learning provides a solution for pH detection. However, most existing studies use one-dimensional convolutional neural networks (1D-CNNs) for spectral analysis, which limits the performance due to insufficient feature extraction. In this work, we propose a 2D triple-branch feature fusion network (TriFNet) for accurate pH determination using surface-enhanced Raman spectra (SERS). Specifically, we design a triple-branch network structure by converting Raman spectra into three types of images to extensively extract complex patterns in spectra. In addition, an attention fusion module, which leverages the complementarity among features in both space and channel, is designed to obtain the valuable information, achieving further accurate pH determination. On our Raman spectral dataset containing 14,137 samples, we achieved mean absolute error (MAE) of 0.059, standard deviation of the absolute error (SD) of 0.07, root mean squared error (RMSE) of 0.092, and coefficient of determination (R2) of 0.991 on the test set. Compared with other published methods, the four metrics showed an average improvement of 47%, 39%, 43%, and 6%, respectively. In addition, visualization validates the diagnostic capability of our model to correlate with biomolecular signatures. Meanwhile, our model has robustness to different SERS chips. These results prove the potential of our method to develop an effective technology based on Raman spectroscopy for accurate pH determination to guide surgery.

A review of clinical use of surface-enhanced Raman scattering-based biosensing for glioma

Glioma is the most common malignant tumor of the nervous system in recent centuries, and the incidence rate of glioma is increasing year by year. Its invasive growth and malignant biological behaviors make it one of the most challenging malignant tumors. Maximizing the resection range (EOR) while minimizing the impact on normal brain tissue is crucial for patient prognosis. Changes in metabolites produced by tumor cells and their microenvironments might be important indicators. As a powerful spectroscopic technique, surface-enhanced Raman scattering (SERS) has many advantages, including ultra-high sensitivity, high specificity, and non-invasive features, which allow SERS technology to be widely applied in biomedicine, especially in the differential diagnosis of malignant tumor tissues. This review first introduced the clinical use of responsive SERS probes. Next, the sensing mechanisms of microenvironment-responsive SERS probes were summarized. Finally, the biomedical applications of these responsive SERS probes were listed in four sections, detecting tumor boundaries due to the changes of pH-responsive SERS probes, SERS probes to guide tumor resection, SERS for liquid biopsy to achieve early diagnosis of tumors, and the application of free-label SERS technology to detect fresh glioma specimens. Finally, the challenges and prospects of responsive SERS detections were summarized for clinical use.

Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects

Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer's and Parkinson's diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research.

Artificial Intelligence for Surface-Enhanced Raman Spectroscopy

Surface-enhanced Raman spectroscopy (SERS), well acknowledged as a fingerprinting and sensitive analytical technique, has exerted high applicational value in a broad range of fields including biomedicine, environmental protection, food safety among the others. In the endless pursuit of ever-sensitive, robust, and comprehensive sensing and imaging, advancements keep emerging in the whole pipeline of SERS, from the design of SERS substrates and reporter molecules, synthetic route planning, instrument refinement, to data preprocessing and analysis methods. Artificial intelligence (AI), which is created to imitate and eventually exceed human behaviors, has exhibited its power in learning high-level representations and recognizing complicated patterns with exceptional automaticity. Therefore, facing up with the intertwining influential factors and explosive data size, AI has been increasingly leveraged in all the above-mentioned aspects in SERS, presenting elite efficiency in accelerating systematic optimization and deepening understanding about the fundamental physics and spectral data, which far transcends human labors and conventional computations. In this review, the recent progresses in SERS are summarized through the integration of AI, and new insights of the challenges and perspectives are provided in aim to better gear SERS toward the fast track.

Global research trends in immunotherapy for glioma: a comprehensive visualization and bibliometric analysis

Background

Glioma is a prevalent and lethal brain malignancy; despite current treatment options, the prognosis remains poor. Therefore, immunotherapy has emerged as a promising therapeutic strategy. However, research trends and hotspots in glioma immunotherapy have not been systematically analyzed. This study aimed to elucidate global research trends and knowledge structures regarding immunotherapy for glioma using bibliometric analysis.

Methods

Publications related to immunotherapy for glioma from 2000-2023 were retrieved from Web of Science Core Collection database (WoSCC). We conducted quantitative analysis and visualization of research trends using various tools, including VOSviewer (1.6.18), CiteSpace (5.7 R3), Microsoft Charticulator, and the Bibliometrix package in R.

Results

A total of 4910 publications were included. The number of annual publications exhibited an obvious upward trend since 2019. The USA was the dominant country in terms of publication output and centrality. Frontiers in Immunology published the most articles. Harvard Medical School ranked first in productivity among institutions. Sampson, John H. Ph.D. is the most prolific author in the field with 88 articles and a total of 7055 citations. Clinical Cancer Research has the largest total number and impact factor. Analysis of keywords showed immunotherapy, glioblastoma, immunotherapy, and clinical trials as hot topics. The tumor microenvironment, cell death pathways, chimeric antigen receptor engineering, tumor-associated macrophages, and nivolumab treatment represent indicating shifts in the direction of future glioma immunotherapy development.

Conclusion

This bibliometric analysis systematically delineated global landscapes and emerging trends in glioma immunotherapy research. This study highlighted the prominence of Chimeric Antigen Receptor T-cell (CAR-T), Programmed Death-1 (PD-1), and nivolumab in current glioma immunotherapy research. The growing emphasis on specific neoantigens and prognostic tumor markers suggests potential avenues for future exploration. Furthermore, the data underscores the importance of strengthened international collaboration in advancing the field.

A Ratiometric SERS Probe for Imaging the Macrophage Phenotypes in Live Mice with Epilepsy and Brain Tumor

Macrophage performs multiple functions such as pathogen phagocytosis, antigen presentation, and tissue remodeling by polarizing toward a spectrum of phenotypes. Dynamic imaging of macrophage phenotypes is critical for evaluating disease progression and the therapeutic response of drug candidates. However, current technologies cannot identify macrophage phenotypes in vivo. Herein, a surface-enhanced Raman scattering nanoprobe, AH1, which enables the accurate determination of physiological pH with high sensitivity and tissue penetration depth through ratiometric Raman signals is developed. Due to the phenotype-dependent metabolic reprogramming, AH1 can effectively identify macrophage subpopulations by measuring the acidity levels in phagosomes. After intravenous administration, AH1 not only visualizes the spatial distribution of macrophage phenotypes in brain tumors and epileptic regions of mouse models, but also reveals the repolarization of macrophages in brain lesions after drug intervention. This work provides a new tool for dynamically monitoring the disease-associated immune microenvironment and evaluating the efficacy of immune-therapeutics in vivo.

Hsp70-Targeting and Size-Tunable Nanoparticles Combine with PD-1 Checkpoint Blockade to Treat Glioma

Invasive glioma usually disrupts the integrity of the blood-brain barrier (BBB), making the delivery of nanodrugs across the BBB possible, but sufficient targeting ability is still avidly needed to improve drug accumulation in glioma. Membrane-bound heat shock protein 70 (Hsp70) is expressed on the membrane of glioma cells rather than adjacent normal cells, therefore it can serve as a specific glioma target. Meanwhile, prolonging the retention in tumors is important for active-targeting nanoparticles to overcome receptor-binding barriers. Herein, the Hsp70-targeting and acid-triggered self-assembled gold nanoparticles (D-A-DA/TPP) are proposed to realize selective delivery of doxorubicin (DOX) to glioma. In the weakly acidic glioma matrix, D-A-DA/TPP formed aggregates to prolong retention, improve receptor-binding efficiency and facilitate acid-responsive DOX release. DOX accumulation in glioma induced immunogenic cell death (ICD) to promote antigen presentation. Meanwhile, combination with the PD-1 checkpoint blockade further activate T cells and provokes robust anti-tumor immunity. The results showed that D-A-DA/TPP can induce more glioma apoptosis. Furthermore, in vivo studies indicated D-A-DA/TPP plus PD-1 checkpoint blockade significantly improved median survival time. This study offeres a potential nanocarrier combining size-tunable strategy with active targeting ability to increase drug enrichment in glioma and synergizes with PD-1 checkpoint blockade to achieve chemo-immunotherapy.

SERS-active plasmonic metal NP-CsPbX3 films for multiple veterinary drug residues detection

Sensitive and multiple veterinary drug residues detection is of important for food safety. Herein, uniform plasmonic Au nanobipyramids@Ag nanorods (Au NBP@Ag NR)-CsPbX₃ films with strong surface-enhanced Raman scattering (SERS) activity were constructed. The effects of different CsPbX₃ (X = Cl, Br, I, or mixed halogens) quantum dots (QDs) on the SERS performances of plasmonic metal NP films were investigated. CsPbI₃ QDs with large dielectric constant could be served as the dielectric media to retard the attenuation of electromagnetic evanescent wave, inducing strong electromagnetic strength for SERS enhancement. Plasmon-induced metal-to-perovskite interfacial charge transfer transition also contributed to SERS enhancement. SERS-active plasmonic Au NBP@Ag NR-CsPbI₃ films had excellent sensitivity and high reproducibility for quantitative, accurate and multiple detection of chloramphenicol, diazepam and malachite green in food matrix. This work deepened the understanding of the SERS enhancement mechanisms of plasmonic metal NP-perovskite hybrid heterostructures, showing potential prospects in food safety monitoring.

Advances in the intraoperative delineation of malignant glioma margin

Surgery plays a critical role in the treatment of malignant glioma. However, due to the infiltrative growth and brain shift, it is difficult for neurosurgeons to distinguish malignant glioma margins with the naked eye and with preoperative examinations. Therefore, several technologies were developed to determine precise tumor margins intraoperatively. Here, we introduced four intraoperative technologies to delineate malignant glioma margin, namely, magnetic resonance imaging, fluorescence-guided surgery, Raman histology, and mass spectrometry. By tracing their detecting principles and developments, we reviewed their advantages and disadvantages respectively and imagined future trends.

Raman spectroscopy: A prospective intraoperative visualization technique for gliomas

The infiltrative growth and malignant biological behavior of glioma make it one of the most challenging malignant tumors in the brain, and how to maximize the extent of resection (EOR) while minimizing the impact on normal brain tissue is the pursuit of neurosurgeons. The current intraoperative visualization assistance techniques applied in clinical practice suffer from low specificity, slow detection speed and low accuracy, while Raman spectroscopy (RS) is a novel spectroscopy technique gradually developed and applied to clinical practice in recent years, which has the advantages of being non-destructive, rapid and accurate at the same time, allowing excellent intraoperative identification of gliomas. In the present work, the latest research on Raman spectroscopy in glioma is summarized to explore the prospect of Raman spectroscopy in glioma surgery.

A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method

Raman spectroscopy is a spectroscopic technique typically used to determine vibrational modes of molecules and is commonly used in chemistry to provide a structural fingerprint by which molecules can be identified. With the help of deep learning, Raman spectroscopy can be analyzed more efficiently and thus provide more accurate molecular information. However, no general neural network is designed for one-dimensional Raman spectral data so far. Furthermore, different combinations of hyperparameters of neural networks lead to results with significant differences, so the optimization of hyperparameters is a crucial issue in deep learning modeling. In this work, we propose a deep learning model designed for Raman spectral data and a hyperparameter optimization method to achieve its best performance, i.e., a method based on the simulated annealing algorithm to optimize the hyperparameters of the model. The proposed model and optimization method have been fully validated in a glioma Raman spectroscopy dataset. Compared with other published methods including linear regression, support vector regression, long short-term memory, VGG and ResNet, the mean squared error is reduced by 0.1557 while the coefficient determination is increased by 0.1195 on average.

Brain-targeting drug delivery systems

Brain diseases, including neurodegenerative diseases, acute ischemic stroke and brain tumors, have become a major health problem and a huge burden on society with high morbidity and mortality. However, most of the current therapeutic drugs can only relieve the symptoms of brain diseases, and it is difficult to achieve satisfactory therapeutic effects fundamentally. Extensive studies have shown that the therapeutic effects of brain diseases are mainly affected by two factors: the conservation of the blood-brain barrier (BBB) and the complexity of the brain micro-environment. Brain-targeting drug delivery systems provide new possibilities for overcoming these barriers with versatility. In this review, it provides an overview of BBB alteration and discusses targeting delivery strategies for brain diseases therapy. Furthermore, delivery systems which are designed to modulate the brain micro-environment with synergistic effects were also highlighted. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Emergence of Responsive Surface-Enhanced Raman Scattering Probes for Imaging Tumor-Associated Metabolites

As a core hallmark of cancer, metabolic reprogramming alters the metabolic networks of cancer cells to meet their insatiable appetite for energy and nutrient. Tumor-associated metabolites, the products of metabolic reprogramming, are valuable in evaluating tumor occurrence and progress timely and accurately because their concentration variations usually happen earlier than the aberrances demonstrated in tissue structure and function. As an optical spectroscopic technique, surface-enhanced Raman scattering (SERS) offers advantages in imaging tumor-associated metabolites, including ultrahigh sensitivity, high specificity, multiplexing capacity, and uncompromised signal intensity. This review first highlights recent advances in the development of stimuli-responsive SERS probes. Then the mechanisms leading to the responsive SERS signal triggered by tumor metabolites are summarized. Furthermore, biomedical applications of these responsive SERS probes, such as the image-guided tumor surgery and liquid biopsy examination for tumor molecular typing, are summarized. Finally, the challenges and prospects of the responsive SERS probes for clinical translation are also discussed.