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The recent outbreak of novel coronavirus (SARS-CoV-2) causing COVID-19 disease spreads rapidly in the world. Rapid and early detection of SARS-CoV-2 facilitates early intervention and prevents the disease spread. Here, we present an All-In-One Dual CRISPR-Cas12a (AIOD-CRISPR) assay for one-pot, ultrasensitive, and visual SARS-CoV-2 detection. By targeting SARS-CoV-2’s nucleoprotein gene, two CRISPR RNAs without protospacer adjacent motif (PAM) site limitation are introduced to develop the AIOD-CRISPR assay and detect the nucleic acids with a sensitivity of few copies. We validate the assay by using COVID-19 clinical swab samples and obtain consistent results with RT-PCR assay. Furthermore, a low-cost hand warmer (~$0.3) is used as an incubator of the AIOD-CRISPR assay to detect clinical samples within 20 min, enabling an instrument-free, visual SARS-CoV-2 detection at the point of care. Thus, our method has the significant potential to provide a rapid, sensitive, one-pot point-of-care assay for SARS-CoV-2. Rapid and early detection of SARS-CoV-2 will aid intervention to stop disease spread. Here the authors present a one-pot CRISPR-based rapid detection system with visual readout.

Different aromatic components do indeed give different tea flavors. There is still little research on whether there is a certain regularity in the combination and content of aromatic components in different aroma types of Phoenix Dancong (PDC) tea. This potential regularity may be a key factor in unraveling the relationship between reproduction and evolution in PDC tea. Here, the 5 kinds of these 4 aroma types PDC tea (Zhuye, Tuofu, Jianghuaxiang, Juduo, Yashixiang) were used as research materials in this study, the headspace solid-phase microextraction combined with gas chromatography–mass spectrometry was used to analyze the aromatic components of these PDC teas. The results showed a total of 36 aromatic components identified in this study. When conducting cluster analysis, it was found that similarity degree arrangement sequence of 5 PDC teas was Juduo, Tuofu, Yashixiang, Zhuye and Jianghuaxiang. Among these aromatic components, the 7,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione, the 2-Cyclopenten-1-one, 3-methyl-2-(2-pentenyl)-,(Z)-, the 2,4-Di-tert-butylphenol, the 3,7-dimethyl-1,5,7-Octatrien-3-ol, and the 2-Furanmethanol,5-ethenyltetrahydro-.alpha.,.alpha.,5-trimethyl-,cis- are common to 5 PDC teas. This study aims to elucidate the similarities in the aromatic components of 5 PDC teas, revealing the major aroma-endowed substances of various aroma, and providing theoretical reference for further exploring the relationship between aroma type discrimination, variety selection, and evolution of PDC teas.

Seaweed phenolics are increasingly recognized for their health-promoting potential, but their bioavailability and interaction with gut microbiota remain insufficiently understood. This study examined the effects of seaweed phenolics on gut microbiota, short-chain fatty acid production and characterized phenolics during colonic fermentation over 48 h. Results showed that Durvillaea potatorum exhibited the highest total phenolic content (3.14 mg GAE/g) after 8 h of fermentation, while Phyllospora comosa showed peak flavonoid content at 0 h (0.73 mg QE/g). Phlorotannin content was notably elevated in D. potatorum at 12 and 48 h. Antioxidant capacity peaked in Cystophora siliquosa at 48 h (FRAP: 0.14 mg TE/g; TAC: 0.62 mg TE/g), whereas radical scavenging activity was highest in Sargassum fallax and P. comosa at 18 and 24 h, respectively (DPPH: 1.15 mg TE/g; ABTS: 0.36 mg TE/g). In this study, seaweed supplementation modulated the microbiota, resulting in alteration in microbial community structure and diversity. Additionally, short chain fatty acids (SCFAs), including acetic acid, butyric acid, isovaleric acid and total fatty acids were significantly elevated in P. comosa at 12 h. These findings suggest that seaweed-derived phenolics may modulate microbial composition and enhancing SCFAs production.

Urine is ideal for non-targeted metabolomics, providing valuable insights into normal and pathological cellular processes. Optimal extraction is critical since non-targeted metabolomics aims to analyse various compound classes. Here, we optimised a low-volume urine preparation procedure for non-targeted GC–MS. Five extraction methods (four organic acid [OA] extraction variations and a “direct analysis” [DA] approach) were assessed based on repeatability, metabolome coverage, and metabolite recovery. The DA method exhibited superior repeatability, and achieved the highest metabolome coverage, detecting 91 unique metabolites from multiple compound classes comparatively. Conversely, OA methods may not be suitable for all non-targeted metabolomics applications due to their bias toward a specific compound class. In accordance, the OA methods demonstrated limitations, with lower compound recovery and a higher percentage of undetected compounds. The DA method was further improved by incorporating an additional drying step between two-step derivatization but did not benefit from urease sample pre-treatment. Overall, this study establishes an improved low-volume urine preparation approach for future non-targeted urine metabolomics applications using GC–MS. Our findings contribute to advancing the field of metabolomics and enable efficient, comprehensive analysis of urinary metabolites, which could facilitate more accurate disease diagnosis or biomarker discovery.

O-antigens of Gram-negative bacteria modulate the interactions of bacterial cells with diverse external factors, including the components of the immune system and bacteriophages. Some phages need to acquire specific adhesins to overcome the O-antigen layer. For other phages, O-antigen is required for phage infection. In this case, interaction of phage receptor binding proteins coupled with enzymatic degradation or modification of the O-antigen is followed by phage infection. Identification of the strategies used by newly isolated phages may be of importance in their consideration for various applications. Here we describe an approach based on screening for host LPS alterations caused by selection by bacteriophages. We describe an optimized LPS profiling procedure that is simple, rapid and suitable for mass screening of mutants. We demonstrate that the phage infection strategies identified using a set of engineered E. coli 4 s mutants with impaired or altered LPS synthesis are in good agreement with the results of simpler tests based on LPS profiling of phage-resistant spontaneous mutants.

This protocol describes a procedure for determining glutathione (GSH) and glutathione disulfide (GSSG) concentrations in blood and other tissues. Artifactual oxidation to GSSG of 5–15% of the GSH found in a sample can occur during deproteination of biological samples with any of the commonly used acids, with consequent marked overestimation of GSSG. This can be prevented by derivatizing GSH with the alkylating agent N -ethylmaleimide (NEM) to form GS-NEM before acid deproteination, followed by back-extraction of excess NEM from the deproteinized samples with dichloromethane. GSSG concentration is then measured by spectrophotometry with the GSH recycling method, on the basis of conversion of GSSG to GSH by glutathione reductase and NADPH and reaction with 5,5′-dithiobis-(2-nitrobenzoic acid). GSH concentration is instead measured by either of two methods: by analysis of GS-NEM conjugates by HPLC in the same sample that is used to measure GSSG or, alternatively, by analysis of GSH by spectrophotometry (GSH recycling method) on one additional sample aliquot that has not been derivatized with NEM. The procedure can assay GSH and GSSG in blood and other tissues in 30 min or less.

Although polymerase chain reaction (PCR) is the most widely used method for DNA amplification, the requirement of thermocycling limits its non-laboratory applications. Isothermal DNA amplification techniques are hence valuable for on-site diagnostic applications in place of traditional PCR. Here we describe a true isothermal approach for amplifying and detecting double-stranded DNA based on a CRISPR–Cas9-triggered nicking endonuclease-mediated Strand Displacement Amplification method (namely CRISDA). CRISDA takes advantage of the high sensitivity/specificity and unique conformational rearrangements of CRISPR effectors in recognizing the target DNA. In combination with a peptide nucleic acid (PNA) invasion-mediated endpoint measurement, the method exhibits attomolar sensitivity and single-nucleotide specificity in detection of various DNA targets under a complex sample background. Additionally, by integrating the technique with a Cas9-mediated target enrichment approach, CRISDA exhibits sub-attomolar sensitivity. In summary, CRISDA is a powerful isothermal tool for ultrasensitive and specific detection of nucleic acids in point-of-care diagnostics and field analyses. Isothermal DNA amplification techniques are useful for diagnostic applications in place of traditional PCR. Here the authors describe CRISDA, which combines CRISPR–Cas9 with strand displacement amplification and exhibits attomolar sensitivity and single-nucleotide specificity in DNA detection.

Acacia senegal (AS) gum (Gum Arabic) is a natural emulsifier exudate from the branches and trunk of Acacia trees and it is recognized by the Food and Drug Administration (FDA) agency as a secure dietary fiber. The present research evaluated the systemic oxidative and necroinflammatory stress induced by CCl 4 administration and the alleviating effect of AS gum aqueous extract (ASE, 7.5 g/Kg b.w.). The results demonstrated the presence of certain phenolic compounds in ASE, as well as its in vitro potent scavenging ability against ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), NO, and lipid peroxide radicals. Also, the outcomes revealed an improvement in the CCl 4 -induced liver, lung, brain, and spleen toxicity by reducing the levels of ROS, lipid peroxidation, NO, and the gene expression of NF-κB and its relevant ROS-mediated inflammatory genes. In contrast, the total antioxidant capacity (TAC), as well as the enzymatic and non-enzymatic antioxidants, were significantly upregulated in these organs after the treatment with ASE. These results were confirmed by improving the morphological features of each organ. Therefore, ASE can ameliorate the systemic toxicity caused by CCl 4 via regulation of the ROS/NF-κB signaling pathway in the rat organs, which is owed to its phytochemical composition.

The need for rapid, accurate, and scalable testing systems for COVID-19 diagnosis is clear and urgent. Here, we report a rapid S calable and Po rtable T esting (SPOT) system consisting of a rapid, highly sensitive, and accurate assay and a battery-powered portable device for COVID-19 diagnosis. The SPOT assay comprises a one-pot reverse transcriptase-loop-mediated isothermal amplification (RT-LAMP) followed by Pf Ago-based target sequence detection. It is capable of detecting the N gene and E gene in a multiplexed reaction with the limit of detection (LoD) of 0.44 copies/μL and 1.09 copies/μL, respectively, in SARS-CoV-2 virus-spiked saliva samples within 30 min. Moreover, the SPOT system is used to analyze 104 clinical saliva samples and identified 28/30 (93.3% sensitivity) SARS-CoV-2 positive samples (100% sensitivity if LoD is considered) and 73/74 (98.6% specificity) SARS-CoV-2 negative samples. This combination of speed, accuracy, sensitivity, and portability will enable high-volume, low-cost access to areas in need of urgent COVID-19 testing capabilities. There is a clear need for rapid, accurate and scalable Covid-19 diagnostics. Here the authors use Pf Ago to detect viral sequences amplified by RT-LAMP in a handheld battery-powered device.

The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models that allow predicting flavor and consumer appreciation. For each beer, we measure over 200 chemical properties, perform quantitative descriptive sensory analysis with a trained tasting panel and map data from over 180,000 consumer reviews to train 10 different machine learning models. The best-performing algorithm, Gradient Boosting, yields models that significantly outperform predictions based on conventional statistics and accurately predict complex food features and consumer appreciation from chemical profiles. Model dissection allows identifying specific and unexpected compounds as drivers of beer flavor and appreciation. Adding these compounds results in variants of commercial alcoholic and non-alcoholic beers with improved consumer appreciation. Together, our study reveals how big data and machine learning uncover complex links between food chemistry, flavor and consumer perception, and lays the foundation to develop novel, tailored foods with superior flavors. Perception and appreciation of food flavour depends on many factors, posing a challenge for effective prediction. Here, the authors combine extensive chemical and sensory analyses of 250 commercial Belgian beers to train machine learning models that enable flavour and consumer appreciation prediction.