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The previous activatable probe toward one analyte can still produce imprecise signal as a result of the challenge cased by accurate identification in complex biological environment. As smarter molecules, dual-locked probes are able to respond to two different analyte with one or more output signals, which display significantly reduced background interference and increased spatial resolution. In this study, a smart cysteine/lipid droplets sequence-activated dual-locked fluorescent probe CN–NO 2 has been designed and synthesized for the detection of tumor tissues. The recognition group of CN–NO 2 removed after reacting with cysteine (Cys) and undergoing intramolecular rearrangement to generate complete fluorophores. This structure had a strong solvent effect; it could recognize lipid droplets (LDs) in cells, thus exhibiting fluorescence without secondary molecular adjustment. The fluorescence of CN–NO 2 was enhanced 1752-fold after double unlocking. Importantly, the unlocking process only takes 10 min. Furthermore, the fluorescence of CN–NO 2 was amplified remarkable and anchored at LDs after reacting with Cys in A549 cells. Therefore, CN–NO 2 clearly indicated the site of mouse xenograft tumor in vivo. Such sequence-activated dual-locked fluorescent probes are envisioned to execute more analysis and diagnostic tasks giving these unique characteristics. • The CN–NO 2 was enhanced 1752-fold after cysteine/lipid droplets double unlocking, and the unlocking process only takes 10 min. [ABSTRACT FROM AUTHOR]

Aiming at the privacy and security issues of sensitive speech data in cloud storage, and how to achieve efficient retrieval with privacy-preserving for encrypted speech data in cloud storage, a searchable encryption over encrypted speech retrieval scheme in cloud storage was proposed. Firstly, the data owner encrypts the original speech data adopting symmetric encryption algorithm Lorenz chaotic mapping. Secondly, the encrypted speech data is uploaded to the cloud server for storage, and meanwhile the Mel frequency cepstrum coefficient (MFCC) features of original speech are extracted as the input of the convolutional neural network (CNN) to execute the deep semantic feature extraction, which is taken as the speech keywords. Finally, the extracted speech keywords are encrypted and stored in the cloud. When the authorized user sends a retrieval request, the trained CNN is utilized to extract the keywords of the speech to be retrieved, and the search trapdoor is generated and sent to the cloud server. In the process of retrieval, the Euclidean distance is used to match the encrypted keywords with the search trapdoor. The theoretical analysis and experimental results show that the proposed scheme has higher security and retrieval accuracy, and can be suitable for the encrypted storage of speech data and efficient secure retrieval. [ABSTRACT FROM AUTHOR]

This work develops a novel photoelectrochemical sensor for the detection of carcinoembryonic antigen (CEA) based on the composite of UCNPs with semiconductors and conformational changes in the DNA structure. Firstly, SnS 2 , ZnIn 2 S 4 and UCNPs were assembled on the surface of the ITO electrode. Then Au NPs were dropped, which could facilitate the coupling of CdSe NPs modified DNA1 via Au–S bond, giving an ITO/SnS 2 /ZnIn 2 S 4 /UCNPs/CdSe heterojunction structure. When irradiated with 980 nm near-infrared (NIR) light, the UV–visible light emitted by the UCNPs could excite the nanocomposite, producing an enhanced photoelectric reaction. Subsequently, CEA aptamer and DNA2-modified SiO 2 were added to form a Y-shaped DNA structure. At this time, the photocurrent was significantly reduced by the combination of the light-blocking effect of SiO 2 and the departure of CdSe NPs from the electrode surface. When the target CEA was added, the recognition between CEA and the aptamer led to the collapse of the Y-shaped DNA structure, the restoration of hairpin DNA and the proximity of CdSe to the electrode. Accordingly, the photocurrent signals enhanced again. Under optimal experimental conditions, the detection limit as low as 0.3 pg mL−1 was obtained with good selectivity, achieving a sensitive "on-off-on" photoelectrochemical sensor for CEA detection. [ABSTRACT FROM AUTHOR]