Virtual Screening and Validation of Affinity DNA Functional Ligands for IgG Fc Segment.

The effective attachment of antibodies to the immune sensing interface is a crucial factor that determines the detection performance of immunosensors. Therefore, this study aims to investigate a novel antibody immobilization material with low molecular weight, high stability, and excellent directional immobilization effect. In this study, we employed molecular docking technology based on the ZDOCK algorithm to virtually screen DNA functional ligands (DNAFL) for the Fc segment of antibodies. Through a comprehensive analysis of the key binding sites and contact propensities at the interface between DNAFL and IgG antibody, we have gained valuable insights into the affinity relationship, as well as the principles governing amino acid and nucleotide interactions at this interface. Furthermore, molecular affinity experiments and competitive binding experiments were conducted to validate both the binding ability of DNAFL to IgG antibody and its actual binding site. Through affinity experiments using multi-base sequences, we identified bases that significantly influence antibody-DNAFL binding and successfully obtained DNAFL with an enhanced affinity towards the IgG Fc segment. These findings provide a theoretical foundation for the targeted design of higher-affinity DNAFLs while also presenting a new technical approach for immunosensor preparation with potential applications in biodetection.

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning.

The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public health protection. The impact of pollen on the identification of bacterial species by Raman and Fourier-Transform Infrared (FTIR) spectra cannot be overlooked. The spectral features of the fourteen class samples were preprocessed and extracted by machine learning algorithms to serve as input data for training purposes. The two types of spectral data were classified using classification models. The partial least squares discriminant analysis (PLS-DA) model achieved classification accuracies of 78.57% and 92.85%, respectively. The Raman spectral data were accurately classified by the support vector machine (SVM) algorithm, with a 100% accuracy rate. The two spectra and their fusion data were correctly classified with 100% accuracy by the random forest (RF) algorithm. The spectral processed algorithms investigated provide an efficient method for eliminating the impact of pollen interference.

Identification and Removal of Pollen Spectral Interference in the Classification of Hazardous Substances Based on Excitation Emission Matrix Fluorescence Spectroscopy.

Sensitively detecting hazardous and suspected bioaerosols is crucial for safeguarding public health. The potential impact of pollen on identifying bacterial species through fluorescence spectra should not be overlooked. Before the analysis, the spectrum underwent preprocessing steps, including normalization, multivariate scattering correction, and Savitzky-Golay smoothing. Additionally, the spectrum was transformed using difference, standard normal variable, and fast Fourier transform techniques. A random forest algorithm was employed for the classification and identification of 31 different types of samples. The fast Fourier transform improved the classification accuracy of the sample excitation-emission matrix fluorescence spectrum data by 9.2%, resulting in an accuracy of 89.24%. The harmful substances, including Staphylococcus aureus, ricin, beta-bungarotoxin, and Staphylococcal enterotoxin B, were clearly distinguished. The spectral data transformation and classification algorithm effectively eliminated the interference of pollen on other components. Furthermore, a classification and recognition model based on spectral feature transformation was established, demonstrating excellent application potential in detecting hazardous substances and protecting public health. This study provided a solid foundation for the application of rapid detection methods for harmful bioaerosols.

Investigating the impact of attenuated fluorescence spectra on protein discrimination.

The optical remote sensing techniques are promising for the real-time detection, and identification of different types of hazardous biological materials. However, the received fluorescent spectra from a remote distance suffer from the atmospheric attenuation effect upon the spectral shape. To investigate the influence of atmospheric attenuation on characterizing, and classifying biological agents, the laboratory-measured fluorescence data of fourteen proteins combined with the atmospheric transmission factors of the MODTRAN model were conducted with different detection ranges. The multivariate analysis techniques of principal component analysis (PCA) and linear discriminant analysis (LDA), and the predictors of Random Forest and XGBoost were employed to assess the separability and distinguishability of different spectra recorded. The results showed that the spectral-shift effect on attenuated spectra varied as a function of the detection range, the atmospheric visibility, and the spectral distribution. According to the PCA and LDA analysis, the distribution of decomposed factors changed in the spectral explanatory power with the increasing attenuation effect, which was consistent with the hierarchical clustering results. Random Forest exhibited higher performance in classifying protein samples than that of XGBoost, while the two methods performed similarly in identifying harmful and harmless subgroups of proteins. Fewer subgroups decreased the sensitivity of the classification accuracy to the attenuation effect. Our analysis demonstrated that combining atmospheric transport models to build a fluorescence spectral database is essential for fast identification between spectra, and reduced classification criteria could facilitate the compatibility of spectral database and classification algorithms.

A photoelectrochemical immunosensor based on magnetic all-solid-state Z-scheme heterojunction for SARS-CoV-2 nucleocapsid protein detection.

Rapid, convenient and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is urgently needed to timely diagnosis of coronavirus pandemic (COVID-19) and control of the epidemic. In this study, a signal-off photoelectrochemical (PEC) immunosensor was constructed for SARS-CoV-2 nucleocapsid (N) protein detection based on a magnetic all-solid-state Z-scheme heterojunction (Fe3O4@SiO2@TiO2@CdS/Au, FSTCA). Integrating the advantages of magnetic materials and all-solid-state Z-scheme heterostructures, FSTCA was implemented to ligate the capture antibody to form magnetic capture probe (FSTCA/Ab1). It can simplify the separation and washing process to improve reproducibility and stability, while allowing immune recognition to be performed in the liquid phase instead of the traditional solid-liquid interface to improve anti-interference. Besides, the heterojunction inhibited the recombination of photogenerated electron/hole (e-/h+) and promoted the light absorption to provide superior photoelectric substrate signal. The mechanism of photogenerated e-/h+ transfer of FSTCA were investigated by the electron spin resonance (ESR) spectroscopy. SiO2 spheres loaded with Au NPs utilized as an efficient signal quencher. The steric hindrance effect of SiO2@Au labeled detection antibodies (SiO2@Au-Ab2) conjugates significantly diminished light absorption and hindered the transfer of photogenerated electrons, further amplifying the signal change value. Based on the above merits, the elaborated immunosensor had a wide linear range of 10 pg mL-1-100 ng mL-1 and a low detection limit down to 2.9 pg mL-1 (S/N = 3). The fabricated PEC immunosensor demonstrated strong anti-interference, easy operation, and high sensitivity, showing enormous potential in clinical diagnosis of SARS-CoV-2.

A Study of the Detection of SARS-CoV-2 by the Use of Electrochemiluminescent Biosensor Based on Asymmetric Polymerase Chain Reaction Amplification Strategy.

A new and reliable method has been constructed for detecting severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) open reading frames 1ab (ORF1ab) gene via highly sensitive electrochemiluminescence (ECL) biosensor technology based on highly efficient asymmetric polymerase chain reaction (asymmetric PCR) amplification strategy. This method uses magnetic particles coupled with biotin-labeled one complementary nucleic acid sequence of the SARS-CoV-2 ORF1ab gene as the magnetic capture probes, and [Formula: see text]-labeled amino-modified another complementary nucleic acid sequence as the luminescent probes, and then a detection model of magnetic capture probes-asymmetric PCR amplification nucleic acid products-[Formula: see text]-labeled luminescent probes is formed, which combines the advantages of highly efficient asymmetric PCR amplification strategy and highly sensitive ECL biosensor technology, enhancing the method sensitivity of detecting the SARS-CoV-2 ORF1ab gene. The method enables the rapid and sensitive detection of the ORF1ab gene and has a linear range of 1-[Formula: see text] copies/[Formula: see text], a regression equation of [Formula: see text] = [Formula: see text] + 2919.301 ([Formula: see text] = 0.9983, [Formula: see text] = 7), and a limit of detection (LOD) of 1 copy/[Formula: see text]. In summary, it can meet the analytical requirements for simulated saliva and urine samples and has the benefits of easy operation, reasonable reproducibility, high sensitivity, and anti-interference abilities, which can provide a reference for developing efficient field detection methods for SARS-CoV-2.

A signal-off photoelectrochemical sandwich-type immunosensor based on WO3/TiO2 Z-scheme heterojunction.

A sandwich "signal-off" type photoelectrochemical (PEC) immunosensor was fabricated based on a composite heterojunction of tungsten oxide/titanium oxide microspheres (WO3/TiO2) acting as signal amplification platform and carbon microspheres loaded by gold nanoparticles (Cs@Au NPs) utilized as the label for detecting antibody. WO3/TiO2 had excellent photoelectric performance, and the results of Mott-Schottky plots, open-circuit voltage, and electron spin resonance spectroscopy indicated that it belonged to the Z-scheme heterojunction transfer mechanism of photogenerated carriers. To achieve the sensitization of PEC immunosensor, Cs@Au NP-labeled immunocomplex can effectively reduce the photocurrent signal. The PEC immunosensors were fabricated under the optimal conditions of 1:1 WO3/TiO2 (molar ratio), 2.0 mg mL-1 WO3/TiO2, and 1.5 mg mL-1 Cs@Au NPs. Through comparison of the detection results of label-free and sandwich-type PEC immunosensors for nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we found that the sensitivity of the sandwich type was 2.53 times the label-free type, and the limit of detection was 0.006 ng mL-1, i.e., 3.17 times lower than the label-free type. This demonstrates that the developed sandwich-type PEC immunosensor will have a brighter application prospect.

Surface Plasmon Resonance Sensor Based on Core-Shell Fe3O4@SiO2@Au Nanoparticles Amplification Effect for Detection of T-2 Toxin.

In this paper, a core-shell based on the Fe3O4@SiO2@Au nanoparticle amplification technique for a surface plasmon resonance (SPR) sensor is proposed. Fe3O4@SiO2@AuNPs were used not only to amplify SPR signals, but also to rapidly separate and enrich T-2 toxin via an external magnetic field. We detected T-2 toxin using the direct competition method in order to evaluate the amplification effect of Fe3O4@SiO2@AuNPs. A T-2 toxin-protein conjugate (T2-OVA) immobilized on the surface of 3-mercaptopropionic acid-modified sensing film competed with T-2 toxin to combine with the T-2 toxin antibody-Fe3O4@SiO2@AuNPs conjugates (mAb-Fe3O4@SiO2@AuNPs) as signal amplification elements. With the decrease in T-2 toxin concentration, the SPR signal gradually increased. In other words, the SPR response was inversely proportional to T-2 toxin. The results showed that there was a good linear relationship in the range of 1 ng/mL~100 ng/mL, and the limit of detection was 0.57 ng/mL. This work also provides a new possibility to improve the sensitivity of SPR biosensors in the detection of small molecules and in disease diagnosis.

Identify the Virus-like Models for COVID-19 as Bio-Threats: Combining Phage Display, Spectral Detection and Algorithms Analysis.

The rapid identification and recognition of COVID-19 have been challenging since its outbreak. Multiple methods were developed to realize fast monitoring early to prevent and control the pandemic. In addition, it is difficult and unrealistic to apply the actual virus to study and research because of the highly infectious and pathogenic SARS-CoV-2. In this study, the virus-like models were designed and produced to replace the original virus as bio-threats. Three-dimensional excitation-emission matrix fluorescence and Raman spectroscopy were employed for differentiation and recognition among the produced bio-threats and other viruses, proteins, and bacteria. Combined with PCA and LDA analysis, the identification of the models for SARS-CoV-2 was achieved, reaching a correction of 88.9% and 96.3% after cross-validation, respectively. This idea might provide a possible pattern for detecting and controlling SARS-CoV-2 from the perspective of combining optics and algorithms, which could be applied in the early-warning system against COVID-19 or other bio-threats in the future.

Performance of Classification Models of Toxins Based on Raman Spectroscopy Using Machine Learning Algorithms.

Rapid and accurate detection of protein toxins is crucial for public health. The Raman spectra of several protein toxins, such as abrin, ricin, staphylococcal enterotoxin B (SEB), and bungarotoxin (BGT), have been studied. Multivariate scattering correction (MSC), Savitzky-Golay smoothing (SG), and wavelet transform methods (WT) were applied to preprocess Raman spectra. A principal component analysis (PCA) was used to extract spectral features, and the PCA score plots clustered four toxins with two other proteins. The k-means clustering results show that the spectra processed with MSC and MSC-SG methods have the best classification performance. Then, the two data types were classified using partial least squares discriminant analysis (PLS-DA) with an accuracy of 100%. The prediction results of the PCA and PLS-DA and the partial least squares regression model (PLSR) perform well for the fingerprint region spectra. The PLSR model demonstrates excellent classification and regression ability (accuracy = 100%, Rcv = 0.776). Four toxins were correctly classified with interference from two proteins. Classification models based on spectral feature extraction were established. This strategy shows excellent potential in toxin detection and public health protection. These models provide alternative paths for the development of rapid detection devices.

A highly sensitive electrochemiluminescence method for abrin detection by a portable biosensor based on a screen-printed electrode with a phage display affibody as specific labeled probe.

Abrin is a highly toxic ribosome-inactivating protein, which could be used as a biological warfare agent and terrorist weapon, and thus needs to be detected efficiently and accurately. Affibodies are a new class of engineered affinity proteins with small size, high affinity, high stability, favorable folding and good robustness, but they have rarely played a role in biological detection. In this work, we establish a novel electrochemiluminescence (ECL) method for abrin detection with a phage display affibody as the specific probe for the first time, to our knowledge, and a portable biosensor based on a screen-printed electrode (SPE) as the testing platform. On the basis of the double antibody sandwich structure in our previous work, we used a phage display affibody instead of monoclonal antibody as a new specific labeled probe. Due to numerous signal molecules labeled on M13 phages, significant signal amplification was achieved in this experiment. Under optimized conditions, a linear dependence was observed from 0.005 to 100 ng/mL with a limit of detection (LOD) of 5 pg/mL. This assay also showed good reproducibility and specificity, and performed well in the detection of simulated samples. Considering its high sensitivity, interference resistance and convenience, this new biosensing system based on phage display affibodies and a portable ECL biosensor holds promise for in situ detection of toxins and pollutants in different environments.

A Potassium Ion-Exchanged Glass Optical Waveguide Sensor Locally Coated with a Crystal Violet-SiO2 Gel Film for Real-Time Detection of Organophosphorus Pesticides Simulant.

An optical waveguide (OWG) sensor was developed for real-time detection of diethyl chlorophosphate (DCP) vapor, which is a typical simulant for organophosphorus pesticides and chemical weapon agents. Silica gel, crystal violet (CV), and potassium ion-exchange (PIE) OWG were used to fabricate the sensor's device. In the real-time detection of the DCP vapor, the volume fraction of DCP vapor was recorded to be as low as 1.68 × 10-9. Moreover, the detection mechanism of CV-SiO2 gel film coated the PIE OWG sensor for DCP, which was evaluated by absorption spectra. These results demonstrated that the change of output light intensity of the OWG sensor significantly increased with the augment of the DCP concentration. Repeatability as well as selectivity of the sensors were tested using 0.042 × 10-6 and 26.32 × 10-6 volume fraction of the DCP vapor. No clear interference with the DCP detection was observed in the presence of other common solvents (e.g., acetone, methanol, dichloromethane, dimethylsulfoxide, and tetrahydrofuran), benzene series (e.g., benzene, toluene, chlorobenzene, and aniline), phosphorus-containing reagents (e.g., dimethyl methylphosphonate and trimethyl phosphate), acid, and basic gas (e.g., acetic acid and 25% ammonium hydroxide), which demonstrates that the OWG sensor could provide real-time, fast, and accurate measurement results for the detection of DCP.

Shufeng Jiedu Capsules Alleviate Lipopolysaccharide-Induced Acute Lung Inflammatory Injury via Activation of GPR18 by Verbenalin.

BACKGROUND/AIMS: Acute respiratory tract infection (ARTI) is the most common reason for outpatient physician office visits. Although powerful and significant in the treatment of infections, antibiotics used for ARTI inappropriately have been an important contributor to antibiotic resistance. We previously reported that Shufeng Jiedu Capsule (SJC) can effectively amplify anti-inflammatory signaling during infection. In this study, we aimed to systematically explore its composition and the mechanism of its effects in ARTI. METHODS: Pseudomonas aeruginosa (PAK) strain was used to generate a mouse model of ARTI, which were then treated with different drugs or compounds to determine the corresponding anti-inflammatory roles. High-performance liquid chromatography-quadrupole time of flight-tandem mass spectrometry. was conducted to detect the chemical compounds in SJC. RNAs from the lung tissues of mice were prepared for microarray analysis to reveal globally altered genes and the pathways involved after SJC treatment. RESULTS: SJC significantly inhibited the expression and secretion of inflammatory factors from PAK-induced mouse lung tissues or lipopolysaccharide-induced peritoneal macrophages. Verbenalin, one of the bioactive compounds identified in SJC, also showed notable anti-inflammatory effects. Microarray data revealed numerous differentially expressed genes among the different treatment groups; here, we focused on studying the role of GPR18. We found that the anti-inflammatory role of verbenalin was attenuated in GPR18 knockout mice compared with wild-type mice, although no statistically significant difference was observed in the untreated PAK-induced mice types. CONCLUSION: Our data not only showed the chemical composition of SJC, but also demonstrated that verbenalin was a significant anti-inflammatory compound, which may function through GPR18.

Detection of Abrin by Electrochemiluminescence Biosensor Based on Screen Printed Electrode.

For the convenience of fast measurement in the outdoor environment, a portable electrochemiluminescence biosensor with the screen-printed electrode as the reaction center was developed, which possesses the characteristics of high sensitivity, small scale, simplified operation and so on, and has been used for in situ detection of abrin. First, combining with magnetic separation technique, the "biotin-avidin" method was used to immobilize the polyclonal antibody (pcAb) on the magnetic microspheres surface as the capture probe. Secondly, the Ru(bpy)32+-labeled monoclonal antibody (mcAb) was used as the specific electrochemiluminescence signal probe. Then, the "mcAb-toxin-pcAb" sandwich model was built to actualize the quantitative detection of abrin on the surface of the screen-printed electrode. The linear detection range was 0.5-1000 ng/mL; the regression equation was Y = 89.251lgX + 104.978 (R = 0.9989, n = 7, p < 0.0001); and the limit of detection (LOD) was 0.1 ng/mL. The sensing system showed high sensitivity, excellent specificity and good anti-interference ability, and could be used for the analysis of trace abrin in various environmental samples with good recovery and reproducibility. Compared with the traditional electrochemiluminescence sensing device, its miniaturization and portability gives it potential to satisfy the requirement of in situ detection.

An Electrochemiluminescence Immunosensor Based on Gold-Magnetic Nanoparticles and Phage Displayed Antibodies.

Using the multiple advantages of the ultra-highly sensitive electrochemiluminescence (ECL) technique, Staphylococcus protein A (SPA) functionalized gold-magnetic nanoparticles and phage displayed antibodies, and using gold-magnetic nanoparticles coated with SPA and coupled with a polyclonal antibody (pcAb) as magnetic capturing probes, and Ru(bpy)3(2+)-labeled phage displayed antibody as a specific luminescence probe, this study reports a new way to detect ricin with a highly sensitive and specific ECL immunosensor and amplify specific detection signals. The linear detection range of the sensor was 0.0001~200 µg/L, and the limit of detection (LOD) was 0.0001 µg/L, which is 2500-fold lower than that of the conventional ELISA technique. The gold-magnetic nanoparticles, SPA and Ru(bpy)3(2+)-labeled phage displayed antibody displayed different amplifying effects in the ECL immunosensor and can decrease LOD 3-fold, 3-fold and 20-fold, respectively, compared with the ECL immunosensors without one of the three effects. The integrated amplifying effect can decrease the LOD 180-fold. The immunosensor integrates the unique advantages of SPA-coated gold-magnetic nanoparticles that improve the activity of the functionalized capturing probe, and the amplifying effect of the Ru(bpy)3(2+)-labeled phage displayed antibodies, so it increases specificity, interference-resistance and decreases LOD. It is proven to be well suited for the analysis of trace amounts of ricin in various environmental samples with high recovery ratios and reproducibility.

Nano-magnetic immunosensor based on staphylococcus protein a and the amplification effect of HRP-conjugated phage antibody.

In this research, super-paramagnetic Fe3O4 nanoparticles (magnetic particles) were coated with Staphylococcus protein A (SPA) and coupled with polyclonal antibody (pcAb) to construct magnetic capturing probes, and HRP-conjugated phage antibody was then used as specific detecting probe to design a labeled immunosensor for trace detection of Staphylococcus aureus enterotoxin B (SEB). The linear detection range of the sensor was 0.008~125 µg/L, the regression equation was Y = 0.487X + 1.2 (R = 0.996, N = 15, p < 0.0001), the limit of detection (LOD) was 0.008 µg/L, and the limit of quantification (LOQ) was 0.008 µg/L. HRP-conjugated phage antibody, SPA and magnetic particles can enhance the sensitivity 4-fold, 3-fold and 2.6-fold higher, respectively. Compared with conventional double-antibody sandwich ELISA, the detection sensitivity of the sensor was 31-fold higher resulting from the integrated amplifying effect. The immunosensor integrates the unique advantages of SPA-oriented antibody as magnetic capturing probe, HRP-conjugated phage antibody as detecting probe, magnetic separation immunoassay technique, and several other advanced techniques, so it achieves high sensitivity, specificity and interference-resistance. It is proven to be well suited for analysis of trace SEB in various environmental samples with high recovery rate and reproducibility.

Solid-state nanochannels based on electro-optical dual signals for detection of analytes.

The sensitive detection of analytes of different sizes is crucial significance for environmental protection, food safety and medical diagnostics. The confined space of nanochannels provides a location closest to the molecular reaction behaviors in real systems, thereby opening new opportunities for the precise detection of analytes. However, due to the susceptibility to external interference on the confined space of nanochannels, the high sensitivity nature of the current signals through the nanochannels is more troubling for the detection reliability. Combining highly sensitive optical signals with the sensitive current signals of solid-state nanochannels establishes a nanochannel detection platform based on electro-optical dual signals, potentially offering more sensitive, specific, and accuracy detection of analytes. This review summarizes the last five years of applications of solid-state nanochannels based on electro-optical dual signals in analytes detection. Firstly, the detection principles of solid-state nanochannels and the construction strategies of nanochannel electro-optical sensing platforms are discussed. Subsequently, the review comprehensively outlines the applications involving nanochannels with electrical signals combined with fluorescence signals, electrical signals combined with surface-enhanced Raman spectroscopy signals, and electrical signals combined with other optical signals in analyte detection. Additionally, the perspectives and difficulties of nanochannels are investigated on the basis of electro-optical dual signals.

A ratiometric fluorescence imprinted sensor based on N-CDs and metal-organic frameworks for visual smart detection of malathion.

Sensitive and rapid detection of pesticide residues in food is essential for human safety. A ratiometric imprinted fluorescence sensor N-CDs@Eu-MOF@MIP (BR@MIP) was constructed to sensitively detect malathion (Mal). Europium-based metal organic frameworks (Eu-MOF) were used as supporters to improve the sensitivity of the BR@MIP. N-doped carbon dots (N-CDs) were used as fluorescent source to produce fluorescent signal. A linear relationship between the concentration of Mal and the fluorescence response of the sensor was found in the Mal concentration range of 1-10 µM with a limit of detection (LOD) of 0.05 µM. Furthermore, the sensor was successfully applied for the detection of Mal in lettuce, tap water, and soil samples, with recoveries in the range of 93.0 % - 99.3 %. Additionally, smartphone-based sensors were used to detect Mal in simulated real samples. Thus, the construction of ratiometric imprinted fluorescence sensor has provided a good strategy for the detection of Mal.

A novel strategy for bioaerosol rapid detection based on broad-spectrum high-efficiency magnetic enrichment and separation combined with ATP bioluminescence.

Bioaerosol detection technology represented by laser-induced fluorescence (LIF) cannot effectively detect bioaerosols in the presence of interferents such as plant-derived smoke, industrial waste gas, pollen and pollen debris which can produce strong non-biological fluorescence interference. To overcome this drawback, in this study, a novel method based on broad-spectrum high-efficiency magnetic enrichment and separation combined with adenosine triphosphate (ATP) bioluminescence was proposed for Escherichia coli (E. coli) bioaerosols rapid detection. First, E. coli bioaerosols mixed with interferents were collected. Core-shell Fe3O4@Polydopamine@Polyethyleneimine magnetic particles were used as bioaerosol enrichment materials to enrich E. coli bioaerosol sampling solutions. Subsequently, an ATP bioluminescence assay was performed to determine the concentration of E. coli. A linear relationship was observed between ATP bioluminescence intensity after enrichment and the E. coli bioaerosol concentration in the range of 870-49,098 particles per liter; the bioluminescence intensity measured after enrichment was significantly higher than that before enrichment, and this enrichment method provide a 6-fold better sensitivity in bioaerosol detection. More importantly, this method efficiently enriched and detected bioaerosols in plant-derived smoke. This method can effectively improve the sensitivity of ATP bioluminescence detection, and possesses the advantages of convenient operation and strong anti-interference ability. It also provides a foundation for the effective detection of bioaerosols mixed with interfering substances, and a reference for evaluating the sensitivity and anti-interference of LIF-based instruments.

CdTe QDs-sensitized TiO2 nanocomposite for magnetic-assisted photoelectrochemical immunoassay of SARS-CoV-2 nucleocapsid protein.

A sensitive, reliable, and cost-effective detection for SARS-CoV-2 was urgently needed due to the rapid spread of COVID-19. Here, a "signal-on" magnetic-assisted PEC immunosensor was constructed for the quantitative detection of SARS-CoV-2 nucleocapsid (N) protein based on Z-scheme heterojunction. Fe3O4@SiO2@Au was used to connect the capture antibody to act as a capture probe (Fe3O4@SiO2@Au/Ab1). It can extract target analytes selectively in complex samples and multiple electrode rinsing and assembly steps were avoided effectively. CdTe QDs sensitized TiO2 coated on the surface of SiO2 spheres to form Z-scheme heterojunction (SiO2@TiO2@CdTe QDs), which broadened the optical absorption range and inhibited the quick recombination of photogenerated electron/hole of the composite. With fascinating photoelectric conversion performance, SiO2@TiO2@CdTe QDs were utilized as a signal label, thus further realizing signal amplification. The migration mechanism of photogenerated electrons was further deduced by active material quenching experiment and electron spin resonance (ESR) measurement. The elaborated immunosensor can detect SARS-CoV-2 N protein in the linear range of 0.005-50 ng mL-1 with a low detection limit of 1.8 pg mL-1 (S/N = 3). The immunosensor displays extraordinary sensitivity, strong anti-interference, and high reproducibility in detecting SARS-CoV-2 N protein, which envisages its potential application in the clinical diagnosis of COVID-19.