Clinical validation of engineered CRISPR/Cas12a for rapid SARS-CoV-2 detection

Background The coronavirus disease (COVID-19) caused by SARS-CoV-2 has swept through the globe at an unprecedented rate. CRISPR-based detection technologies have emerged as a rapid and affordable platform that can shape the future of diagnostics. Methods We developed ENHANCEv2 that is composed of a chimeric guide RNA, a modified LbCas12a enzyme, and a dual reporter construct to improve the previously reported ENHANCE system. We validated both ENHANCE and ENHANCEv2 using 62 nasopharyngeal swabs and compared the results to RT-qPCR. We created a lyophilized version of ENHANCEv2 and characterized its detection capability and stability. Results Here we demonstrate that when coupled with an RT-LAMP step, ENHANCE detects COVID-19 samples down to a few copies with 95% accuracy while maintaining a high specificity towards various isolates of SARS-CoV-2 against 31 highly similar and common respiratory pathogens. ENHANCE works robustly in a wide range of magnesium concentrations (3 mM-13 mM), allowing for further assay optimization. Our clinical validation results for both ENHANCE and ENHANCEv2 show 60/62 (96.7%) sample agreement with RT-qPCR results while only using 5 µL of sample and 20 minutes of CRISPR reaction. We show that the lateral flow assay using paper-based strips displays 100% agreement with the fluorescence-based reporter assay during clinical validation. Finally, we demonstrate that a lyophilized version of ENHANCEv2 shows high sensitivity and specificity for SARS-CoV-2 detection while reducing the CRISPR reaction time to as low as 3 minutes while maintaining its detection capability for several weeks upon storage at room temperature. Conclusions CRISPR-based diagnostic platforms offer many advantages as compared to conventional qPCR-based detection methods. Our work here provides clinical validation of ENHANCE and its improved form ENHANCEv2 for the detection of COVID-19.

High-performance near-infrared photodetectors based on gate-controlled graphene–germanium Schottky junction with split active junction

The structure of a gate-controlled graphene/germanium hybrid photodetector was optimized by splitting the active region to achieve highly sensitive infrared detection capability. The strengthened internal electric field in the split active junctions enabled efficient collection of photocarriers, resulting in a responsivity of 2.02 A W−1 and a specific detectivity of 5.28 × 1010 Jones with reduced dark current and improved external quantum efficiency; these results are more than doubled compared with the responsivity of 0.85 A W−1 and detectivity of 1.69 × 1010 Jones for a single active junction device. The responsivity of the optimized structure is 1.7, 2.7, and 39 times higher than that of previously reported graphene/Ge with Al2O3 interfacial layer, gate-controlled graphene/Ge, and simple graphene/Ge heterostructure photodetectors, respectively.

Tin oxide/Silicon Heterojunction with Nano Litchi Shell Structure for Ultrafast, High-Detectivity, Self-Powered Broadband Photodetectors

Self-powered photodetectors with excellent figure-of-merits, fast response speed, and broadband detection capability have drawn tremendous research interest. However, it is still challenging to develop excellent light-absorbing materials as photodetectors with...

Ground Validation Experiment and Spectral Detection Capability Evaluation of Mars Mineralogical Spectrometer (MMS) Aboard HX-1 Orbiter

As a hyperspectral imager aboard the orbiter “HX-1” of China’s first Mars mission, the Mars Mineralogical Spectrometer (MMS) is designed with hyperspectral and multispectral operation modes to survey the mineral types and their distribution on the surface of Mars, and to study the overall chemical composition and evolution history of Mars. The multispectral modes of MMS are different from hyperspectral modes on the bands selection, spatial and spectral resolution, Signal-to-Noise Ratio (SNR) etc. So the spectral detection capability of each mode of MMS is also different. The ground validation experiment of MMS is conducted to evaluate the hyperspectral and multispectral data quality and detection capabilities. The main conclusions include: (1) The measured hyperspectra of typical mineral samples obtained by MMS agree well with the data acquired by the Standard Comparison Spectrometers (SCS) under the same measurement conditions, and the spectral uncertainty between MMS and SCS is less than 7% in the key spectral ranges ($0.7\sim2.2~\upmu \text{m}$ 0.7 ∼ 2.2 μm ). For some typical minerals, the absorption band positions deviation between MMS and SCS are within $0.69\sim14.86~\text{nm}$ 0.69 ∼ 14.86 nm , which are within the spectral resolution limits of MMS. (2) The six sets of band combinations designed for MMS multispectral modes are slightly superior to CRISM’s multispectral mode in terms of spectral resolutions and bands selection, the water-containing minerals will be more accurately distinguished and identified, such as montmorillonite and kaolinite. Besides, the SNR of each multispectral mode is greater than 400 in the 500–2600 nm spectral range, which meets the requirements for the subtle spectral characteristics of water-containing minerals. (3) Benefiting from the MMS ground validation experiment and the experience of the OMEGA and CRISM, it is recommended that MMS first adopt the spatial continuous 52-sample or 104-sample (spatial resolution is about $0.53\sim1.06~\text{km}$ 0.53 ∼ 1.06 km ) multispectral operation mode for typical minerals global mapping and finding target areas of interest. Then the 208-sample multispectral mode (spatial resolution is about $\sim265~\text{m}$ ∼ 265 m ) or 26-sample hyperspectral mode can be used to survey target areas of interest for the subtle mineral types characteristics and distribution. At last, 26-sample hyperspectral mode could be used to monitor the atmospheric composition of Mars by limb observations.

NanoGram Detection of Drilling Fluids Additives for Uncertainty Reduction in Surface Logging

Manual sampling rock cuttings off the shale shaker for lithology and petrophysical characterization is frequently performed during mud logging. Knowing the depth origin where the cuttings were generated is very important for correlating the cuttings to the petrophysical characterization of the formation. It is a challenge to accurately determine the depth origin of the cuttings, especially in horizontal sections and in coiled tubing drilling, where conventional logging while drilling is not accessible. Additionally, even in less challenging drilling conditions, many factors can contribute to an inaccurate assessment of the depth origin of the cuttings. Inaccuracies can be caused by variation of the annulus dimension used to determine the lag time (and thus the depth of the cuttings), by the shifting or scrambling of cuttings during their return trip back to the surface, and by the mislabelling of the cuttings during sampling. In this work, we report the synthesis and application of polystyrenic nanoparticles (NanoTags) in labeling cuttings for depth origin assessment. We have successfully tagged cuttings using two NanoTags during a drilling field test in a carbonate gas well and demonstrated nanogram detection capability of the tags via pyrolysis-GCMS using an internally developed workflow. The cuttings depth determined using our tags correlates well with the depth calculated by conventional mud logging techniques.

Pocket Mercury-Vapour Detection System Employing a Preconcentrator Based on Au-TiO2 Nanomaterials

In environments polluted by mercury vapors that are potentially harmful to human health, there is a need to perform rapid surveys in order to promptly identify the sources of emission. With this aim, in this work, a low cost, pocket-sized portable mercury measurement system, with a fast response signal is presented. It consists of a preconcentrator, able to adsorb and subsequently release the mercury vapour detected by a quartz crystal microbalance (QCM) sensor. The preconcentrator is based on an adsorbing layer of titania/gold nanoparticles (TiO2NP/AuNPs), deposited on a micro-heater that acts as mercury thermal desorption. For the detection of the released mercury vapour, gold electrodes QCM (20 MHz) have been used. The experimental results, performed in simulated polluted mercury-vapour environments, showed a detection capability with a prompt response. In particular, frequency shifts (−118 Hz ± 2 Hz and −30 Hz ± 2 Hz) were detected at concentrations of 65 µg/m3 Hg0 and 30 µg/m3 Hg0, with sampling times of 60 min and 30 min, respectively. A system limit of detection (LOD) of 5 µg/m3 was evaluated for the 30 min sampling time.

Vector Magnetic Anomaly Detection via an Attention Mechanism Deep-Learning Model

Magnetic anomaly detection (MAD) is used for detecting moving ferromagnetic targets. In this study, we present an end-to-end deep-learning model for magnetic anomaly detection on data recorded by a single static three-axis magnetometer. We incorporate an attention mechanism into our network to improve the detection capability of long time-series signals. Our model has good performance under the Gaussian colored noise with the power spectral density of 1/fα, which is similar to the field magnetic noise. Our method does not require another magnetometer to eliminate the effects of the Earth’s magnetic field or external interferences. We evaluate the network’s performance through computer simulations and real-world experiments. The high detection performance and the single magnetometer implementation show great potential for real-time detection and edge computing.

A new LC–MS/MS method for multiple residues/contaminants in bovine meat

A multi-class and multi-residue/contaminant method for the determination of veterinary drug and pesticide residues and mycotoxins in bovine meat has been developed and validated. The veterinary drug residues/contaminants included antimicrobials, anabolic hormones, lactones, β-agonists, mycotoxins, and pesticides. Isotopic labeled internal standards were included to compensate residual matrix effects. The calibrators used in the method demonstrated linearity with the R2 > 0.98. The decision limit (CCα) values were in the range from 0.067 to 2103.84 μg/kg, while the range for detection capability (CCβ) was from 0.083 to 2482.13 μg/kg. The limit of detection (LOD) and limit of quantification (LOQ) were in the range from 0.059 to 291.36 μg/kg, and 0.081 to 328.13 μg/kg, respectively. The recovery of analytes ranged from 61.28% to 116.20%. The intra-day coefficient of variation (CV) was from 0.97 to 25.93% and the inter-day CV was 2.30–34.04%. The method has been used for the determination of 49 residues/contaminants in bovine meat. Application of the method in routine analysis in bovine samples, revealed in limited samples the presences of enrofloxacin, oxytetracycline and sulfadiazine at the concentration of 35.22 µg/kg, 27.35 µg/kg, and 36.20 µg/kg, respectively.