Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial...Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.展开更多
This article presented a facile fabrication process for polydimethylsiloxane(PDMS)composite gold nanotris⁃octahedra(Au NTOH)for a flexible SERS sensor with high sensitivity.Specifically,Au NTOH with excellent SERS beh...This article presented a facile fabrication process for polydimethylsiloxane(PDMS)composite gold nanotris⁃octahedra(Au NTOH)for a flexible SERS sensor with high sensitivity.Specifically,Au NTOH with excellent SERS behaviors was synthesized using a seed-mediated growth method and the dimensions of the Au NTOH was easily tuned.In addition,the influence of size on the SERS performance of their monolayers was systematically investigated,and the Au NTOH with the size of 61 nm possessed the best SERS performance.Importantly,a hydrophilic-substrateassisted interfacial self-assembled monolayer transfer technique was proposed to transfer Au NTOH onto PDMS films,resulting in forming flexible and transparent Au NTOH@PDMS substrates.Furthermore,the excellent signal homoge⁃neity of this substrate was demonstrated and the sensitivity was verified by a measurement of crystal violet(CV)as low as 1×10^(-8) mol/L.As a result,this SERS sensor is progressing for applying in the identification of trace contaminants in broad fields.展开更多
Bacterial infection is a major threat to global public health,and can cause serious diseases such as bacterial skin infection and foodborne diseases.It is essential to develop a new method to rapidly diagnose clinical...Bacterial infection is a major threat to global public health,and can cause serious diseases such as bacterial skin infection and foodborne diseases.It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time.In this work,we developed a 4-mercaptophenylboronic acid gold nanoparticles(4-MPBA-AuNPs)-functionalized hydrogel microneedle(MPBA-H-MN)for bacteria detection in skin interstitial fluid.MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min.Surface enhanced Raman spectroscopy(SERS)detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria.Overall,the capture efficiency of this method exceeded 50%.In the concentration range of 1×10_(7) to 1×10^(10) colony-forming units/mL(CFU/mL),the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration.Using random forest(RF)-based machine learning,bacteria were effectively distinguished with an accuracy of 97.87%.In addition,the harmless disposal of used MNs by photothermal ablation was convenient,environmentally friendly,and inexpensive.This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.展开更多
Deep learning neural network incorporating surface enhancement Raman scattering technique(SERS)is becoming as a powerful tool for the precise classifications and diagnosis of bacterial infections.However,the large amo...Deep learning neural network incorporating surface enhancement Raman scattering technique(SERS)is becoming as a powerful tool for the precise classifications and diagnosis of bacterial infections.However,the large amount of sample requirement and time-consuming sample collection severely hinder its applications.We herein propose a spectral concatenation strategy for residual neural network using nonspecific and specific SERS spectra for the training data augmentation,which is accessible to acquiring larger training dataset with same number of SERS spectra or same size of training dataset with fewer SERS spectra,compared with pure non-specific SERS spectra.With this strategy,the training loss exhibit rapid convergence,and an average accuracy up to 100%in bacteria classifications was achieved with50 SERS spectra for each kind of bacterium;even reduced to 20 SERS spectra per kind of bacterium,classification accuracy is still>95%,demonstrating marked advantage over the results without spectra concatenation.This method can markedly improve the classification accuracy under fewer samples and reduce the data collection workload,and can evidently enhance the performance when used in different machine learning models with high generalization ability.Therefore,this strategy is beneficial for rapid and accurate bacteria classifications with residual neural network.展开更多
Male infertility affects 10-15%of couples globally,with azoospermia-complete absence of sperm-accounting for 15%of cases.Traditional diagnostic methods for azoospermia are subjective and variable.This study presents a...Male infertility affects 10-15%of couples globally,with azoospermia-complete absence of sperm-accounting for 15%of cases.Traditional diagnostic methods for azoospermia are subjective and variable.This study presents a novel,noninvasive,and accurate diagnostic method using surface-enhanced Raman spectroscopy(SERS)combined with machine learning to analyze seminal plasma exosomes.Semen samples from healthy controls(n=32)and azoospermic patients(n=22)were collected,and their exosomal SERS spectra were obtained.Machine learning algorithms were employed to distinguish between the SERS pro files of healthy and azoospermic samples,achieving an impressive sensitivity of 99.61%and a speci ficity of 99.58%,thereby highlighting signi ficant spectral differences.This integrated SERS and machine learning approach offers a sensitive,label-free,and objective diagnostic tool for early detection and monitoring of azoospermia,potentially enhancing clinical outcomes and patient management.展开更多
Ultrasensitive detection of multiple diseases markers is of great importance in improving diagnostic accuracy,precision,and efficiency.A versatile Au nanozyme Raman probe strategy was employed to develop an ultrasensi...Ultrasensitive detection of multiple diseases markers is of great importance in improving diagnostic accuracy,precision,and efficiency.A versatile Au nanozyme Raman probe strategy was employed to develop an ultrasensitive multiplex surface-enhanced Raman scattering(SERS)immunosensor using encoded silica photonic crystal beads(SPCBs).The efficient Au nanozyme Raman probe strategy was constructed using a robust Au nanozyme with high dual enzyme-like activity and SERS activity.On the one hand,Au nanozyme tags with oxidase-like activity can catalyze the oxidation of Raman-inactive 3,3,5,5-tetramethylbenzidine(TMB)to Raman-active oxidized TMB(ox-TMB)in the presence of O_(2).On the other hand,Au nanozyme tags with peroxidase-like activity can catalyze Raman-inactive TMB to Ramanactive ox-TMB in the presence of H_(2)O_(2).This dual catalysis action results in many Raman-active reporter molecules(ox-TMB)enabling highly sensitive detection.Meanwhile,the Au nanozyme as an extraordinary SERS substrate further enhances the detection signals of these Raman reporter molecules.Using reflection peaks of different SPCBs to encode tumor markers,an ultrasensitive multiplex SERS immunosensor was developed for detection of carcinoembryonic antigen(CEA)and alpha-fetoprotein(AFP),which exhibited wide linear ranges of 0.001-100 ng/m L for CEA and 0.01-1000 ng/m L for AFP,accompanied by low detection limits of 0.66 pg/m L for CEA and 9.5 pg/m L for AFP,respectively.This work demonstrates a universal and promising nanozyme Raman probe strategy to develop ultrasensitive multiplex SERS immunosensors for precise clinical diagnosis of disease.展开更多
Ovarian cancer is a prevalent gynecological malignancy with high mortality and low survival rates.The absence of specific symptoms in early stages often leads to late-stage diagnoses.Standard treatment typically inclu...Ovarian cancer is a prevalent gynecological malignancy with high mortality and low survival rates.The absence of specific symptoms in early stages often leads to late-stage diagnoses.Standard treatment typically includes surgery followed by platinum and paclitaxel chemotherapy.Exosomes,nanoscale vesicles released by various cell types,are key in intercellular communication,carrying biologically active molecules like proteins,lipids,enzymes,mRNA,and miRNAs.They are involved in tumor microenvironment remodeling,angiogenesis,metastasis,and chemoresistance in ovarian cancer.Emerging research highlights exosomes as drug carriers and therapeutic targets to suppress anti-tumor immune responses.Surface-enhanced Raman scattering(SERS)enables multiplexed,sensitive,and rapid detection of exosome surface proteins,offering advantages such as low background noise,no photobleaching,robustness,and high sensitivity over other detection methods.This review explores the relationship between exosomes and chemoresistance in ovarian cancer,examining the mechanisms by which exosomes contribute to drug resistance and their clinical implications.The goal is to provide new insights into chemoresistance mechanisms,improve diagnosis and intervention strategies,and enhance chemotherapy sensitivity in clinical treatments.In addition,the prospects of exosomes as drug carriers to resist chemical resistance and improve the survival of ovarian cancer patients are summarized.This article emphasizes the role of SERS in detecting ovarian cancer exosomes and advances in exosome detection.展开更多
基金supported by the projects funded by the Education Department of Shaanxi Provincial Government(NO.23JP116)the Natural Science Fund of Shaanxi Province(NO.2024JC-YBMS-396)+3 种基金the National Natural Science Foundation of China(NO.52171191,52371198,U22A20137)the Constructing National Independent Innovation Demonstration Zones(XM2024XTGXQ05)Shenzhen Science and Technology Innovation Program(JCYJ20220818102215033,GJHZ20210705142542015,JCYJ20220530160811027)Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization(2023B1212060012).
文摘Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.
基金The National Natural Science Foundation of China(12274055)the Fundamental Research Funds for the Central Universities(04442024072)the Training Program of Innovation and Entrepreneurship for Undergraduates in Dalian Minzu University(202312026063)。
文摘This article presented a facile fabrication process for polydimethylsiloxane(PDMS)composite gold nanotris⁃octahedra(Au NTOH)for a flexible SERS sensor with high sensitivity.Specifically,Au NTOH with excellent SERS behaviors was synthesized using a seed-mediated growth method and the dimensions of the Au NTOH was easily tuned.In addition,the influence of size on the SERS performance of their monolayers was systematically investigated,and the Au NTOH with the size of 61 nm possessed the best SERS performance.Importantly,a hydrophilic-substrateassisted interfacial self-assembled monolayer transfer technique was proposed to transfer Au NTOH onto PDMS films,resulting in forming flexible and transparent Au NTOH@PDMS substrates.Furthermore,the excellent signal homoge⁃neity of this substrate was demonstrated and the sensitivity was verified by a measurement of crystal violet(CV)as low as 1×10^(-8) mol/L.As a result,this SERS sensor is progressing for applying in the identification of trace contaminants in broad fields.
基金supported by the National Natural Science Foundation of China(Grant Nos.:82204340,82173954,and 82073815)the Natural Science Foundation of Jiangsu Province,China(Grant No.:BK20221048)+1 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent,China(Grant No.:2022ZB295)Key Laboratory Project of Quality Control of Chinese Herbal Medicines and Decoction Pieces,Gansu Institute for Drug Control,China(Grant No.:2024GSMPA-KL02).
文摘Bacterial infection is a major threat to global public health,and can cause serious diseases such as bacterial skin infection and foodborne diseases.It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time.In this work,we developed a 4-mercaptophenylboronic acid gold nanoparticles(4-MPBA-AuNPs)-functionalized hydrogel microneedle(MPBA-H-MN)for bacteria detection in skin interstitial fluid.MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min.Surface enhanced Raman spectroscopy(SERS)detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria.Overall,the capture efficiency of this method exceeded 50%.In the concentration range of 1×10_(7) to 1×10^(10) colony-forming units/mL(CFU/mL),the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration.Using random forest(RF)-based machine learning,bacteria were effectively distinguished with an accuracy of 97.87%.In addition,the harmless disposal of used MNs by photothermal ablation was convenient,environmentally friendly,and inexpensive.This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.
基金supported by the National Key Research and Development Program of China(No.2023YFC3402900)the National Nature Science of Foundation(No.61875131)+1 种基金Shenzhen Key Laboratory of Photonics and Biophotonics(No.ZDSYS20210623092006020)Shenzhen Science and Technology Innovation Program(No.20231120175730001)。
文摘Deep learning neural network incorporating surface enhancement Raman scattering technique(SERS)is becoming as a powerful tool for the precise classifications and diagnosis of bacterial infections.However,the large amount of sample requirement and time-consuming sample collection severely hinder its applications.We herein propose a spectral concatenation strategy for residual neural network using nonspecific and specific SERS spectra for the training data augmentation,which is accessible to acquiring larger training dataset with same number of SERS spectra or same size of training dataset with fewer SERS spectra,compared with pure non-specific SERS spectra.With this strategy,the training loss exhibit rapid convergence,and an average accuracy up to 100%in bacteria classifications was achieved with50 SERS spectra for each kind of bacterium;even reduced to 20 SERS spectra per kind of bacterium,classification accuracy is still>95%,demonstrating marked advantage over the results without spectra concatenation.This method can markedly improve the classification accuracy under fewer samples and reduce the data collection workload,and can evidently enhance the performance when used in different machine learning models with high generalization ability.Therefore,this strategy is beneficial for rapid and accurate bacteria classifications with residual neural network.
基金support from the National Natural Science Foundation of China(No.62275049)the Natural Science Foundation of Fujian Province,China(No.2022J02024)the Fujian Province Joint Fund Project for Scientific and Technological Innovation(2023Y9383).
文摘Male infertility affects 10-15%of couples globally,with azoospermia-complete absence of sperm-accounting for 15%of cases.Traditional diagnostic methods for azoospermia are subjective and variable.This study presents a novel,noninvasive,and accurate diagnostic method using surface-enhanced Raman spectroscopy(SERS)combined with machine learning to analyze seminal plasma exosomes.Semen samples from healthy controls(n=32)and azoospermic patients(n=22)were collected,and their exosomal SERS spectra were obtained.Machine learning algorithms were employed to distinguish between the SERS pro files of healthy and azoospermic samples,achieving an impressive sensitivity of 99.61%and a speci ficity of 99.58%,thereby highlighting signi ficant spectral differences.This integrated SERS and machine learning approach offers a sensitive,label-free,and objective diagnostic tool for early detection and monitoring of azoospermia,potentially enhancing clinical outcomes and patient management.
基金financially supported by National Natural Science Foundation of China(Nos.21475116,21575125 and 22474124)the National Natural Science Foundation of Jiangsu Province(Nos.BK20221370,BK20211362)+5 种基金Key University Natural Science Foundation of Jiangsu-Province(No.20KJA150004)the Project for Science and Technology of Yangzhou(No.YZ2022074)the Project for Yangzhou City and Yangzhou University corporation(No.YZ2023204)Cross cooperation project of Subei Peoples’Hospital of Jiangsu Province(No.SBJC220009)the Open Research Fund of State Key Laboratory of Analytical Chemistry for Life Science(No.SKLACLS2405)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX24_3728)。
文摘Ultrasensitive detection of multiple diseases markers is of great importance in improving diagnostic accuracy,precision,and efficiency.A versatile Au nanozyme Raman probe strategy was employed to develop an ultrasensitive multiplex surface-enhanced Raman scattering(SERS)immunosensor using encoded silica photonic crystal beads(SPCBs).The efficient Au nanozyme Raman probe strategy was constructed using a robust Au nanozyme with high dual enzyme-like activity and SERS activity.On the one hand,Au nanozyme tags with oxidase-like activity can catalyze the oxidation of Raman-inactive 3,3,5,5-tetramethylbenzidine(TMB)to Raman-active oxidized TMB(ox-TMB)in the presence of O_(2).On the other hand,Au nanozyme tags with peroxidase-like activity can catalyze Raman-inactive TMB to Ramanactive ox-TMB in the presence of H_(2)O_(2).This dual catalysis action results in many Raman-active reporter molecules(ox-TMB)enabling highly sensitive detection.Meanwhile,the Au nanozyme as an extraordinary SERS substrate further enhances the detection signals of these Raman reporter molecules.Using reflection peaks of different SPCBs to encode tumor markers,an ultrasensitive multiplex SERS immunosensor was developed for detection of carcinoembryonic antigen(CEA)and alpha-fetoprotein(AFP),which exhibited wide linear ranges of 0.001-100 ng/m L for CEA and 0.01-1000 ng/m L for AFP,accompanied by low detection limits of 0.66 pg/m L for CEA and 9.5 pg/m L for AFP,respectively.This work demonstrates a universal and promising nanozyme Raman probe strategy to develop ultrasensitive multiplex SERS immunosensors for precise clinical diagnosis of disease.
基金Special thanks go to the National Natural Science Foundation for Youth,China(Grant No.:82202648)the Introduce High-Level Talent Incentive Project,China(Grant No.:0103-31021200052)for their financial support,which made this work possible.
文摘Ovarian cancer is a prevalent gynecological malignancy with high mortality and low survival rates.The absence of specific symptoms in early stages often leads to late-stage diagnoses.Standard treatment typically includes surgery followed by platinum and paclitaxel chemotherapy.Exosomes,nanoscale vesicles released by various cell types,are key in intercellular communication,carrying biologically active molecules like proteins,lipids,enzymes,mRNA,and miRNAs.They are involved in tumor microenvironment remodeling,angiogenesis,metastasis,and chemoresistance in ovarian cancer.Emerging research highlights exosomes as drug carriers and therapeutic targets to suppress anti-tumor immune responses.Surface-enhanced Raman scattering(SERS)enables multiplexed,sensitive,and rapid detection of exosome surface proteins,offering advantages such as low background noise,no photobleaching,robustness,and high sensitivity over other detection methods.This review explores the relationship between exosomes and chemoresistance in ovarian cancer,examining the mechanisms by which exosomes contribute to drug resistance and their clinical implications.The goal is to provide new insights into chemoresistance mechanisms,improve diagnosis and intervention strategies,and enhance chemotherapy sensitivity in clinical treatments.In addition,the prospects of exosomes as drug carriers to resist chemical resistance and improve the survival of ovarian cancer patients are summarized.This article emphasizes the role of SERS in detecting ovarian cancer exosomes and advances in exosome detection.
