Label-free bacterial colony detection and viability assessment by continuous-wave terahertz transmission imaging

Isolation of Antagonistic Endophytic Fungi from Postharvest Chestnuts and Their Biocontrol on Host Fungal Pathogens

In this study, antagonistic endophytic fungi were isolated from postharvest chestnut fruits; endophytic antagonistic fungi and their combination of inhibitory effects on the fungal pathogen Neofusicoccum parvum were evaluated. A total of 612 endophytic fungi were isolated from 300 healthy chestnut kernels, and 6 strains out of them including NS-3, NS-11, NS-38, NS-43, NS-56, and NS-58 were confirmed as antagonistic endophytic fungi against Neofusicoccum parvum; these were separately identified as Penicillium chermesinum, Penicillium italicum, Penicillium decaturense, Penicillium oxalicum, Talarmyces siamensis, and Penicillium guanacastense. Some mixed antagonistic endophytic fungi, such as NS-3-38, NS-11-38, NS-43-56, and NS-56-58-38, exhibited a much stronger antifungal activity against N. parvum than that applied individually. Among them, the mixture of NS-3-38 showed the highest antifungal activity, and the inhibition rate was up to 86.67%. The fermentation broth of NS-3, NS-38, and their combinations exhibited an obvious antifungal activity against N. parvum, and the ethyl acetate phase extract of NS-3-38 had the strongest antifungal activity, for which the inhibitory rate was up to 90.19%. The NS-3-38 fermentation broth combined with a chitosan coating significantly reduced N. parvum incidence in chestnuts from 100% to 19%. Furthermore, the fruit decay and weight loss of chestnuts during storage were significantly decreased by the NS-3-38 fermentation broth mixture along with a chitosan coating. Therefore, a mixture of P. chermesinum and P. decaturense could be used as a potential complex biocontrol agent to control postharvest fruit decay in chestnuts.

Terahertz imaging for non-invasive classification of healthy and cimiciato-infected hazelnuts

The development of new non-invasive approaches able to recognize defective food is currently a lively field of research. In particular, a simple and non-destructive method able to recognize defective hazelnuts, such as cimiciato-infected ones, in real-time is still missing. This study has been designed to detect the presence of such damaged hazelnuts. To this aim, a measurement setup based on terahertz (THz) radiation has been developed. Images of a sample of 150 hazelnuts have been acquired in the low THz range by a compact and portable active imaging system equipped with a 0.14 THz source and identified as Healthy Hazelnuts (HH) or Cimiciato Hazelnut (CH) after visual inspection. All images have been analyzed to find the average transmission of the THz radiation within the sample area. The differences in the distribution of the two populations have been used to set up a classification scheme aimed at the discrimination between healthy and injured samples. The performance of the classification scheme has been assessed through the use of the confusion matrix on 50 samples. The False Positive Rate (FPR) and True Negative Rate (TNR) are 0% and 100%, respectively. On the other hand, the True Positive Rate (TPR) and False Negative Rate (FNR) are 75% and 25%, respectively. These results are relevant from the perspective of the development of a simple, automatic, real-time method for the discrimination of cimiciato-infected hazelnuts in the processing industry.

THz-ATR Spectroscopy Integrated with Species Recognition Based on Multi-Classifier Voting for Automated Clinical Microbial Identification

The demand for rapid and accurate identification of microorganisms is growing due to considerable importance in all areas related to public health and safety. Here, we demonstrate a rapid and label-free strategy for the identification of microorganisms by integrating terahertz-attenuated total reflection (THz-ATR) spectroscopy with an automated recognition method based on multi-classifier voting. Our results show that 13 standard microbial strains can be classified into three different groups of microorganisms (Gram-positive bacteria, Gram-negative bacteria, and fungi) by THz-ATR spectroscopy. To detect clinical microbial strains with better differentiation that accounts for their greater sample heterogeneity, an automated recognition algorithm is proposed based on multi-classifier voting. It uses three types of machine learning classifiers to identify five different groups of clinical microbial strains. The results demonstrate that common microorganisms, once time-consuming to distinguish by traditional microbial identification methods, can be rapidly and accurately recognized using THz-ATR spectra in minutes. The proposed automatic recognition method is optimized by a spectroscopic feature selection algorithm designed to identify the optimal diagnostic indicator, and the combination of different machine learning classifiers with a voting scheme. The total diagnostic accuracy reaches 80.77% (as high as 99.6% for Enterococcus faecalis) for 1123 isolates from clinical samples of sputum, blood, urine, and feces. This strategy demonstrates that THz spectroscopy integrated with an automatic recognition method based on multi-classifier voting significantly improves the accuracy of spectral analysis, thereby presenting a new method for true label-free identification of clinical microorganisms with high efficiency.

Rapid measurement of waterborne bacterial viability based on difunctional gold nanoprobe

Rapid measurement of waterborne bacterial viability is crucial for ensuring the safety of public health. Herein, we proposed a colorimetric assay for rapid measurement of waterborne bacterial viability based on a difunctional gold nanoprobe (dGNP). This versatile dGNP is composed of bacteria recognizing parts and signal indicating parts, and can generate color signals while recognizing bacterial suspensions of different viabilities. This dGNP-based colorimetric assay has a fast response and can be accomplished within 10 min. Moreover, the proposed colorimetric method is able to measure bacterial viability between 0% and 100%. The method can also measure the viability of other bacteria including Staphylococcus aureus, Shewanella oneidensis, and Escherichia coli O157H7. Furthermore, the proposed method has acceptable recovery (95.5–104.5%) in measuring bacteria-spiked real samples. This study offers a simple and effective method for the rapid measurement of bacterial viability and therefore should have application potential in medical diagnosis, food safety, and environmental monitoring.

A colorimetric method is proposed to measure waterborne bacterial viability by using a difunctional gold nanoprobe that can generate color signals while recognizing bacterial suspensions of different viabilities.

Continuous-Wave THz Imaging for Biomedical Samples

In the past few decades, the applications of terahertz (THz) spectroscopy and imaging technology have seen significant developments in the fields of biology, medical diagnosis, food safety, and nondestructive testing. Label-free diagnosis of malignant tumours has been obtained and also achieved significant development in THz biomedical imaging. This review mainly presents the research status and prospects of several common continuous-wave (CW) THz medical imaging systems and applications of THz medical imaging in biological tissues. Here, we first introduce the properties of THz waves and how these properties play a role in biomedical imaging. Then, we analyse both the advantages and disadvantages of the CW THz imaging methods and the progress of these methods in THz biomedical imaging in recent ten years. Finally, we summarise the obstacles in the way of the application of THz bio-imaging application technology in clinical detection, which need to be investigated and overcome in the future.

Diagnosis of hepatocellular carcinoma based on a terahertz signal and VMD-CWSE

A novel strategy on combining variational mode decomposition (VMD) and composite weighted-scale sample entropy (CWSE) modified from composite multiscale entropy (CMSE) is proposed to screen hepatocellular carcinoma (HCC) by measuring the terahertz (THz) pulse signals of ten normal and ten HCC serums. Eight measured HCC specimens are negative in serum biomarker alpha fetoprotein (AFP) determination. In CWSE, the time series with weighted-scales are generated from the weighted average processing in the coarse-grained time series corresponding to each scale of the CMSE algorithm. VMD served as a preprocessing method was introduced into decomposing THz signal to obtain the mode functions of specific bandwidth for identification. Final results reveal that more obtainable entropy values of CWSE for recognition in comparison to those of CMSE on the basis of the rule of statistically significant difference and effect size and also manifest the stronger discriminability than the traditional THz parameters. This study provides a new potential auxiliary tool for diagnosis HCC and develops the methodology on the discrimination for similar THz signals.

Highly sensitive detection of Staphylococcus aureus by a THz metamaterial biosensor based on gold nanoparticles and rolling circle amplification

A highly sensitive method for detecting Staphylococcus aureus (S. aureus) is urgently needed to reduce the impact and spread of hospital-acquired infections and food-borne illness. For this purpose, this paper presents a THz metamaterial biosensor based on gold nanoparticles (AuNPs) and rolling circle amplification (RCA). The RCA process amplified the S. aureus DNA fragments and generated copious yields of long single-strand DNA molecules. These molecules were then conjugated with the AuNPs to form complexes that delivered exceptional increases in the refractive indices of the samples, and resulted in corresponding improvements in the THz response of the metamaterial. Under optimal conditions, the shifts in the metamaterial's resonance frequency displayed a linear relationship with concentrations of synthetic S. aureus DNA in the range from 10 fM to 10 pM, with a limit of detection of 2.77 fM. We also tested the practical application of this biosensor in measurements of genomic DNA in clinical bacterial strains, where the sensor showed a detection limit of 0.08 pg μL⁻¹ and a linear range from 0.1 to 5 pg μL⁻¹. It also exhibited reasonable specificity, resisting interference from three other pathogenic bacteria. These findings indicate that the proposed approach offers a cost-effective THz biosensing strategy that can be easily fabricated and conveniently operated to aid the diagnosis of infectious disease and food safety control.

A highly sensitive method for detecting Staphylococcus aureus (S. aureus) is urgently needed to reduce the impact and spread of hospital-acquired infections and food-borne illness.