Enzymatic Desialylation Enables Reliable Charge Variant Characterization of Highly Glycosylated and Sialylated Fc Fusion Proteins DOI Creative Commons
Xiaona Wen, Anita P. Liu, Jing Song

et al.

ACS Pharmacology & Translational Science, Journal Year: 2025, Volume and Issue: 8(2), P. 394 - 408

Published: Jan. 23, 2025

Fusion proteins constitute a class of engineered therapeutics and have emerged as promising candidates for disease treatment. However, the structural complexity heterogeneity fusion make their characterization extremely challenging, thus, an innovative comprehensive analytical toolbox is needed. Here, first time, we demonstrate novel robust workflow to evaluate charge variants highly glycosylated protein with heavy sialylation using imaged capillary isoelectric focusing (icIEF). In development icIEF method, key factors that were systematically investigated include desialylation level, stability desialylated molecule, incubation time temperature desialylation, concentrations, urea l-arginine effects on tertiary structure, instrumental comparability. Multivariate correlation analyses subsequently applied confirm impacts parameters evaluated. Furthermore, microfluidic chip-based system coupled ultraviolet detection mass spectrometry (icIEF-UV/MS) was utilized identify critical post-translational modifications ameliorate understanding variants. Our study demonstrates this enables mechanistic heavily sialylated therapeutics.

Language: Английский

RSPSSL: A novel high-fidelity Raman spectral preprocessing scheme to enhance biomedical applications and chemical resolution visualization DOI Creative Commons

Jiaqi Hu,

Jinna Chen,

Chenlong Xue

et al.

Light Science & Applications, Journal Year: 2024, Volume and Issue: 13(1)

Published: Feb. 20, 2024

Abstract Raman spectroscopy has tremendous potential for material analysis with its molecular fingerprinting capability in many branches of science and technology. It is also an emerging omics technique metabolic profiling to shape precision medicine. However, precisely attributing vibration peaks coupled specific environmental, instrumental, specimen noise problematic. Intelligent spectral preprocessing remove statistical bias sample-related errors should provide a powerful tool valuable information extraction. Here, we propose novel scheme based on self-supervised learning (RSPSSL) high capacity fidelity. can preprocess arbitrary spectra without further training at speed ~1 900 per second human interference. The experimental data trial demonstrated excellent signal fidelity 88% reduction root mean square error 60% infinite norm ( $${L}_{{\infty }}$$ L ∞ ) compared established techniques. With this advantage, it remarkably enhanced various biomedical applications 400% accuracy elevation (ΔAUC) cancer diagnosis, average 38% (few-shot) 242% improvement paraquat concentration prediction, unsealed the chemical resolution hyperspectral images, especially fingerprint region. preprocessed from different devices, laboratories, diverse applications. This will enable mechanism screening label-free volumetric imaging organism disease metabolomics scenario throughput, cross-device, analyte complexity,

Language: Английский

Citations

24
Plasmonic nanoparticle sensors: current progress, challenges, and future prospects DOI Creative Commons
Krishna Kant, Reshma Beeram, Yi Cao

et al.

Nanoscale Horizons, Journal Year: 2024, Volume and Issue: 9(12), P. 2085 - 2166

Published: Jan. 1, 2024

This comprehensive review summarizes the past, present, and future of plasmonic NP-based sensors in terms different sensing platforms, chemical biological analytes, expected technologies.

Language: Английский

Citations

19
Surface-enhanced Raman scattering for the detection of biomarkers of neurodegenerative diseases: A review DOI
Chentao Li,

Yinglin Wang,

Yafang Wu

et al.

TrAC Trends in Analytical Chemistry, Journal Year: 2025, Volume and Issue: 185, P. 118173 - 118173

Published: Feb. 3, 2025

Language: Английский

Citations

2
SERSomes for metabolic phenotyping and prostate cancer diagnosis DOI Creative Commons
Xinyuan Bi,

Jiayi Wang,

Bingsen Xue

et al.

Cell Reports Medicine, Journal Year: 2024, Volume and Issue: 5(6), P. 101579 - 101579

Published: May 21, 2024

Molecular phenotypic variations in metabolites offer the promise of rapid profiling physiological and pathological states for diagnosis, monitoring, prognosis. Since present methods are expensive, time-consuming, still not sensitive enough, there is an urgent need approaches that can interrogate complex biological fluids at a system-wide level. Here, we introduce hyperspectral surface-enhanced Raman spectroscopy (SERS) to profile microliters biofluidic metabolite extraction 15 min with spectral set, SERSome, be used describe structures functions various molecules produced biofluid specific time via SERS characteristics. The differences biofluids, including cell culture medium human serum, successfully profiled, showing diagnosis accuracy 80.8% on internal test set 73% external validation prostate cancer, discovering potential biomarkers, predicting tissue-level aggressiveness. SERSomes promising methodology metabolic phenotyping.

Language: Английский

Citations

17
Label-Free Multiplex Profiling of Exosomal Proteins with a Deep Learning-Driven 3D Surround-Enhancing SERS Platform for Early Cancer Diagnosis DOI
Miao Chen,

Haoyang Wang,

Yibin Zhang

et al.

Analytical Chemistry, Journal Year: 2024, Volume and Issue: 96(17), P. 6794 - 6801

Published: April 16, 2024

Identification of protein profiling on plasma exosomes by SERS can be a promising strategy for early cancer diagnosis. However, it is still challenging to detect multiple exosomal proteins simultaneously since the Raman signals detected conventional colloidal nanocrystals or two-dimensional substrates are incomplete and complex. Herein, we develop novel three-dimensional (3D) surround-enhancing platform, named 3D se-SERS, multiplex detection proteins. In this covered with "hotspots" generated gold nanoparticles, which surround analytes densely three-dimensionally, providing sensitive comprehensive signals. Combining se-SERS deep learning model, successfully quantitatively profiled seven including CD63, CD81, CD9, CD151, CD171, TSPAN8, PD-L1 surface from patients, predict occurrence advancement lung cancer. This integrating technique benefits high sensitivity significant multiplexing ability analysis exosomes, demonstrating potential learning-driven technology exosome-based

Language: Английский

Citations

12
Applications of Raman spectroscopy in clinical medicine DOI Creative Commons
Yaping Qi,

Esther Xinyi Chen,

Dan Hu

et al.

Food Frontiers, Journal Year: 2024, Volume and Issue: 5(2), P. 392 - 419

Published: Jan. 10, 2024

Abstract Raman spectroscopy is a nondestructive and highly effective technique for analyzing biological tissues diagnosing diseases by providing detailed spectral information about the specific molecular structures of substances. Its efficacy in these applications has been widely recognized, making it powerful tool field. This article presents comprehensive overview latest developments its wide‐ranging diagnosis critical diseases, such as cancer, infections, neurodegenerative predicting surgical outcomes. It highlights significant contributions areas, shedding light on potential valuable diagnostic tool. delves into advancements biomedical sciences, with focus state‐of‐the‐art techniques surface‐enhanced spectroscopy, resonance tip‐enhanced spectroscopy. These have shown great various within The explores their use ex vivo medical diagnosis, covering topics sample collection, data processing, successful establishment correlations between spectra biochemical diseases. Furthermore, discusses limitations current research offers insights future directions further exploration field sciences.

Language: Английский

Citations

11
3D hotspot engineering and analytes strategy enabled ultrasensitive SERS platform for biosensing of depression biomarker DOI

Minyao Wang,

Zhongze Lou,

Yanbin Hou

et al.

Biosensors and Bioelectronics, Journal Year: 2024, Volume and Issue: 250, P. 116059 - 116059

Published: Jan. 22, 2024

Language: Английский

Citations

10
Electrode- and Label-Free Assessment of Electrophysiological Firing Rates through Cytochrome C Monitoring via Raman Spectroscopy DOI Creative Commons
Christian Tentellino, Marta d’Amora, Rustamzhon Melikov

et al.

ACS Sensors, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

In vitro neurotoxicology aims to assess and predict the side effects of exogenous chemicals toward human brain. Among exploited approaches, electrophysiological techniques stand out for high spatiotemporal resolution sensitivity, with patch clamp considered gold standard technique such purposes. However, structural toxicity metabolic may elude detection when only electrical activity is measured, highlighting need integrating recordings complementary approaches as optical methods. this study, we describe an integrated platform recording neuronal performing chemical analysis a noninvasive label-free imaging, Raman spectroscopy. Specifically, developed protocol that maximizes signal-to-noise ratio while avoiding crosstalk spectroscopical readouts any phototoxicity associated laser exposure. Synchronous sequential electrical–optical measurements were carried compared, approach being more suitable longitudinal investigation correlation intracellular content reduced cytochrome C, lipids, proteins, nucleic acids. Data shows strong between status single cells overall firing rate, suggesting electrode- assessment rates through monitoring C via spectroscopy multielectrode array devices noise impedance are used. Conversely, rate not correlated Thus, study demonstrates downstream upstream features de novo synthesis acids, provides additional information accurate acute chronic neurotoxicity.

Language: Английский

Citations

1
Raman imaging as a window into cellular complexity: a future perspective DOI
Katsumasa Fujita

Nature Methods, Journal Year: 2025, Volume and Issue: 22(5), P. 890 - 892

Published: May 1, 2025

Language: Английский

Citations

1
Carbon‐based nanodots for biomedical applications and clinical transformation prospects DOI Creative Commons

Haizhen Ding,

Tenghui Xiao,

Fangfang Ren

et al.

BMEMat, Journal Year: 2024, Volume and Issue: 2(3)

Published: May 11, 2024

Abstract Carbon dots (CDs), emerging as a promising class of nanomaterials, have garnered significant interest in the field biomedicine due to their unique physicochemical properties. This review provides comprehensive overview recent advancements biomedical applications CDs, emphasizing potential for revolutionizing diagnostics, therapy, and bio‐imaging. We discuss synthesis functionalization which are pivotal tailoring properties specific applications. The CDs bioimaging include fluorescence imaging, magnetic resonance photoacoustic etc. Additionally, this delves into benefits treatment diseases including cancer, inflammation Alzheimer's, Finally, we look forward future biomedicine, necessity interdisciplinary collaboration overcome current obstacles facilitate clinical translation CDs‐based technologies. aims provide summary perspectives on latest developments hoping inspire further research rapidly advancing field.

Language: Английский

Citations

7