From Lab to Home: Ultrasensitive Rapid Detection of SARS-CoV-2 with a Cascade CRISPR/Cas13a-Cas12a System Based Lateral Flow Assay.

Currently, CRISPR/Cas-based molecular diagnostic techniques usually rely on the introduction of nucleic acid amplification to improve their sensitivity, which is usually more time-consuming, susceptible to aerosol contamination, and therefore not suitable for at-home molecular testing. In this research, we developed an advanced CRISPR/Cas13a-Cas12a-based lateral flow assay that facilitated the ultrasensitive and rapid detection of SARS-CoV-2 RNA directly from samples, without the need for nucleic acid amplification. This method was called CRISPR LFA enabling at-home RNA testing (CLEAR). CLEAR used a novel cascade mechanism with specially designed probes that fold into hairpin structures, enabling visual detection of SARS-CoV-2 sequences down to 1 aM sensitivity levels. More importantly, CLEAR had a positive coincidence rate of 100% and a negative coincidence rate of 100% for clinical nasopharyngeal swabs from 16 patients. CLEAR was particularly suitable for at-home molecular testing, providing a low-cost, user-friendly solution that can efficiently distinguish between different SARS-CoV-2 variants. CLEAR overcame the common limitations of high sensitivity and potential contamination associated with traditional PCR-based systems, making it a promising tool for widespread public health application, especially in environments with limited access to laboratory resources.

Research on cognitive impairment and potential risk factors in peritoneal dialysis patients: An observational study.

The objective of this study is to investigate the associated risk factors and their effects on cognitive impairment (CI) in patients undergoing peritoneal dialysis. A retrospective analysis was conducted on the basic information of 268 patients who underwent continuous ambulatory peritoneal dialysis (CAPD) at our hospital from January 2020 to September 2023. Cognitive function was assessed using the Montreal Cognitive Assessment Scale during their subsequent dialysis visits. Participants were categorized into a CI group and a cognitively normal group. Blood and other biological samples were collected for relevant biomarker analysis. Subsequently, we analyzed and compared the factors influencing CI between the 2 groups. The prevalence of CI among CAPD patients was 58.2%. Compared to the cognitively normal group, the CI group had a higher prevalence of alcohol consumption, lower levels of education, and reduced serum uric acid levels (P < .05). There was also a higher incidence of autoimmune diseases such as systemic lupus erythematosus in the CI group (P < .05). In terms of dialysis efficacy, the residual kidney Kt/V and residual kidney Ccr were significantly lower in the CI group compared to the cognitively normal group. In blood parameters, the CI group showed elevated total cholesterol levels and lower serum calcium concentrations (P < .05). Logistic regression analysis identified male gender, older age, lower educational attainment, hypercholesterolemia, and elevated high-sensitivity C-reactive protein levels as independent risk factors for CI in CAPD patients (P < .05). Additionally, in this patient cohort, dialysis duration and residual renal function were protective factors against CI (P < .05). CI is prevalent among PD patients. Elevated high-sensitivity C-reactive protein levels, male gender, older age, lower educational attainment, and hypercholesterolemia constitute an independent risk factor for CI in CAPD patients, whereas residual renal function acts as a protective element.

Water-assisted oxidative redispersion of Cu particles through formation of Cu hydroxide at room temperature.

Sintering of active metal species often happens during catalytic reactions, which requires redispersion in a reactive atmosphere at elevated temperatures to recover the activity. Herein, we report a simple method to redisperse sintered Cu catalysts via O2-H2O treatment at room temperature. In-situ spectroscopic characterizations reveal that H2O induces the formation of hydroxylated Cu species in humid O2, pushing surface diffusion of Cu atoms at room temperature. Further, surface OH groups formed on most hydroxylable support surfaces such as γ-Al2O3, SiO2, and CeO2 in the humid atmosphere help to pull the mobile Cu species and enhance Cu redispersion. Both pushing and pulling effects of gaseous H2O promote the structural transformation of Cu aggregates into highly dispersed Cu species at room temperature, which exhibit enhanced activity in reverse water gas shift and preferential oxidation of carbon monoxide reactions. These findings highlight the important role of H2O in the dynamic structure evolution of supported metal nanocatalysts and lay the foundation for the regeneration of sintered catalysts under mild conditions.

Influence of Social Distance on Foreign Language Effect in Moral Judgment.

Previous research has shown that moral choice depends on language, a phenomenon known as the moral foreign language effect (mFLE). The current study examines the influence of social distance on the mFLE. In Experiment 1, 200 participants were randomly assigned to either close or distant social distance in English or Chinese. In Experiment 2, 188 participants were randomly assigned to either English or Chinese and were presented with eight moral dilemmas, each with five different levels of social distance. After reading the dilemma, participants made a choice on a binary scale (Yes/No) in both Experiments 1 and 2 or on a more sensitive 100-point scale in Experiment 2. The results showed that the mFLE was present in distant social distance but absent in close social distance. Finally, a meta-analysis of the results from both studies confirmed the effect of social distance on the mFLE. These findings demonstrate that social distance might play an important role in moderating the mFLE in moral judgment.

Integrated phase separation in microliter droplets for ultratrace-enriching biomarker analysis.

Ultratrace-enriching biomarker analysis is an effective method for achieving highly accurate and enhanced sensitive detection. In this study, we have developed an enrichment detection platform by combining a minipillar array with an aqueous two-phase system (ATPS) for ultratrace enriching biomarker analysis. After optimizing the enrichment conditions of ATPS, target miRNAs at ultratrace levels specifically accumulate in the DEX-rich phase, which significantly increases the target miRNA concentration-related fluorescence intensity. Compared to non-enriched miRNA in the single-phase PEG solution, the detection limit of ATPS-enriched miRNA had improved more than 200-fold. The ATPS-based enrichment detection strategy offers a novel and convenient approach for the simultaneous detection of biomarkers with ultratrace.

Computer Vision-Based Biomass Estimation for Invasive Plants.

We report on the detailed steps of a method to estimate the biomass of invasive plants based on UAV remote sensing and computer vision. To collect samples from the study area, we prepared a sample square assembly to randomize the sampling points. An unmanned aerial camera system was constructed using a drone and camera to acquire continuous RGB images of the study area through automated navigation. After completing the shooting, the aboveground biomass in the sample frame was collected, and all correspondences were labeled and packaged. The sample data was processed, and the aerial images were segmented into small images of 280 x 280 pixels to create an image dataset. A deep convolutional neural network was used to map the distribution of Mikania micrantha in the study area, and its vegetation index was obtained. The organisms collected were dried, and the dry weight was recorded as the ground truth biomass. The invasive plant biomass regression model was constructed using the K-nearest neighbor regression (KNNR) by extracting the vegetation index from the sample images as an independent variable and integrating it with the ground truth biomass as a dependent variable. The results showed that it was possible to predict the biomass of invasive plants accurately. An accurate spatial distribution map of invasive plant biomass was generated by image traversal, allowing precise identification of high-risk areas affected by invasive plants. In summary, this study demonstrates the potential of combining unmanned aerial vehicle remote sensing with machine learning techniques to estimate invasive plant biomass. It contributes significantly to the research of new technologies and methods for real-time monitoring of invasive plants and provides technical support for intelligent monitoring and hazard assessment at the regional scale.