The epidermal growth factor receptor (EGFR) plays an important role in the proliferation of various cancers, and the expression level of EGFR in tumor tissues can provide a basis for the diagnosis and prognosis. Improving the detection technology of EGFR to achieve high sensitivity and faster speed will benefit the diagnosis of many types of tumors. Trace biological samples can be sensitively measured with terahertz (THz) metamaterial devices. Here, a bow-tie array THz metamaterial biosensor is presented and modified with gold nanoparticles (GNPs) and EGFR antibodies for specific EGFR detection. The effect of the size of the GNP on the sensitivity enhancement was also analyzed. Enhanced sensing for EGFR was achieved with the assistance of GNPs and EGFR antibodies. Importantly, the metamaterial functionalized by GNPs and antibodies with a bigger GNP diameter achieves a greater resonance frequency shift. The proposed metamaterial biosensor can also realize tiny-volume EGFR solution detection. Our proposed technique can therefore sense EGFR sensitively with high speed, and can potentially be applied to achieve quick and accurate detection of EGFR related tumors.

We demonstrate an automatic recognition strategy for terahertz (THz) pulsed signals of breast invasive ductal carcinoma (IDC) based on a wavelet entropy feature extraction and a machine learning classifier. The wavelet packet transform was implemented into the complexity analysis of the transmission THz signal from a breast tissue sample. A novel index of energy to Shannon entropy ratio (ESER) was proposed to distinguish different tissues. Furthermore, the principal component analysis (PCA) method and machine learning classifier were further adopted and optimized for automatic classification of the THz signal from breast IDC sample. The areas under the receiver operating characteristic curves are all larger than 0.89 for the three adopted classifiers. The best breast IDC recognition performance is with the precision, sensitivity and specificity of 92.85%, 89.66% and 96.67%, respectively. The results demonstrate the effectiveness of the ESER index together with the machine learning classifier for automatically identifying different breast tissues.

In recent decades, terahertz (THz) radiation has been widely applied in many chemical and biomedical areas. Due to its ability to resolve the absorption features of many compounds non-invasively, it is a promising technique for chemical recognition of substances such as drugs or explosives. A key challenge for THz technology is to be able to accurately classify spectral measurements acquired in unknown complicated environments, rather than those from ideal laboratory conditions. Support vector machine (SVM) and deep neural networks (DNN) are powerful and widely adopted approaches for complex classification with a high accuracy. In this paper, we explore and apply the SVM and DNN methods for classifying the frequency spectra of glucose and lactose. We measured 372 groups of independent signals under different conditions to provide a sufficient training set. The classification accuracies achieved were 99% for the SVM method and 89.6% for the DNN method. These high classification accuracies demonstrate great potential in chemical recognition.

Controlling the polarization state of an optical pulse within a short gating time facilitates ultrafast all-optical data processing and recording. Using the innovative all-optical modulation method such as the transient terahertz Kerr effect (TKE), the polarization state of the optical pulse can be switched within the gating time on the sub-picosecond scale. In this work, we use high-frequency single-cycle terahertz (THz) pulses to excite the Kerr effects of materials and explore the potential to shorten the gating time of the polarization modulator. A low-density polyethylene (LDPE) material with good Kerr-related properties is proposed to improve the performance of the TKE-based modulator and the obtained ultrafast gating time (FWHM) can reach 86 fs. Experimental evidence for the thickness dependence of the Kerr response demonstrates that the errors caused by optical transmission factors in the LDPE medium can be ignored, and thus the ultrafast gating modulation is mainly limited by the duration of probe pulse. Compared with common TKE-based materials, we believe that the low-cost LDPE is a good candidate to achieve high-power TKE-based ultrafast pulse switching.

The CLP Publishing collects CLP journals and partnered optics and photonics journals, and provides readers an optical publishing platform with global influence. SPIE, OSA, CUP. Chinese Laser Press (CLP), established by Shanghai Institute of Optics and Fine Mechanics (SIOM), Chinese Academy of Sciences (CAS) and Chinese Optical Society (COS) in 2009, nowadays publishes eight journals and manages three online platforms.

We examine the terahertz (THz) emission from air filament driven by two-color lasers with relatively longer wavelengths than 800 nm. The THz energy dependence on the input laser energy increases more rapidly with a longer laser wavelength, and the scaling laws of THz energy as a function of fundamental wavelength vary for different optical powers, which is theoretically validated by considering the optical wavelength-dependent ionization rate. Furthermore, the THz polarization undergoes a continuous rotation as a function of the laser wavelength, since the relative phase and polarization of the two pulses are adjusted through changing the excitation wavelength in the frequency doubling crystal. Our results contribute to the understanding of THz wave generation in a femtosecond laser filament and suggest a practical way to control the polarization of terahertz pulses for potential applications.