Dumbbell probe initiated multi-rolling circle amplification assisted CRISPR/Cas12a for highly sensitive detection of clinical microRNA.

A novel miRNA detection technique named Dumbbell probe initiated multi-Rolling Circle Amplification assisted CRISPR/Cas12a (DBmRCA) was developed relying on the ligation-free dumbbell probe and the high-sensitivity CRISPR/Cas12a signal out strategy. This DBmRCA assay streamlines miRNA quantification within a mere 30-min timeframe and with exceptional analytical precision. The efficacy of this method was validated by assessing miRNA levels in clinical samples, revealing distinct expression panel of miR-200a and miR-126 in lung cancer/adjacent/normal tissue specimens. Moreover, a predictive model was established to classify benign and malignant tumor. Due to its time efficiency, enhanced sensitivity, and streamlined workflow, this assay would be a reliable tool for miRNA analysis in clinical settings, offering potential guidance for early diagnosis and treatment of lung cancer.

Examination of a practical method to quantitatively evaluate the rolling over movement in a clinical setting.

[Purpose] We investigated the utility of wearable inertial and magnetic sensing modules for analyzing neck and trunk movements during the rolling over movement. [Participants and Methods] The participants were instructed to roll over from the supine to the side-lying position with three sensor units attached to their forehead, xiphoid process of the sternum, and abdomen. Experiments were conducted on two prescribed patterns: one emphasizing hip joint flexion and adduction, and the other focusing on scapular protraction and horizontal shoulder joint adduction in two healthy participants (one male and one female). The flexion and rotation angles of the neck and trunk were calculated using conventional spreadsheet software with data obtained from the sensors. The obtained values were compared for agreement with those derived from a three-dimensional (3D) motion analysis device. [Results] The cross-correlation coefficient for the flexion and rotation angles of the neck and trunk between the two measurement methods was approximately 0.85, and the root mean square (RMS) angle difference was approximately 5.0°. [Conclusion] Wearable inertial and magnetic sensors can be used to quantitatively evaluate neck and trunk movements during the rolling over movement.

The day after mowing: Time and type of mowing influence grassland arthropods.

Recent losses in the abundance and diversity of arthropods have been documented in many regions and ecosystems. In grasslands, such insect declines are largely attributed to land use, including modern machinery and mowing regimes. However, the effects of different mowing techniques on arthropods remain poorly understood. Using 11 years of data from 111 agricultural grassland plots across Germany, we analyzed the influence of various grassland management variables on the abundance and abundance-accounted species richness of four arthropod orders: Araneae, Coleoptera, Hemiptera, and Orthoptera. The analysis focused on detailed mowing information, for example, days after mowing and mower type, and compared their effect with other aspects of grassland management, that is, rolling, leveling, fertilization, and grazing. We found strong negative effects of mowing on all four arthropod orders, with arthropod abundance being lowest directly after mowing and steadily increasing to three to seven times the abundance after 100 days post-mowing. Likewise, Hemiptera and Coleoptera species richness was 30% higher 100 days after mowing. Mower width showed a positive effect on Orthoptera abundance, but not on the other arthropods. Arthropod abundance and Coleoptera species richness were lowest when a mulcher was used compared to rotary or bar mowers. In addition to mowing, intensive grazing negatively affected Orthoptera abundance but not the other orders. Mowing represents a highly disturbing and iterative stressor with negative effects on arthropod abundance and diversity, likely contributed by mowing-induced mortality and habitat alteration. While modifications of mowing techniques such as mower type or mowing height and width may help to reduce the negative impact of mowing on arthropods, our results show that mowing itself has the most substantial negative effect. Based on our results, we suggest that reduced mowing frequency, omission of mowing in parts of the grassland (refuges), or extensive grazing instead of mowing have the greatest potential to promote arthropod populations.

Experimental selection of rolling contact length to the average thickness (L\have) ratio for producing fine-grain Incoloy 907 superalloy sheet by hot-rolling.

The current study investigates the effects of L\have values on the microstructure and tensile properties of the superalloy Incoloy 907. These effects are studied using hot-rolling at 84 % and 96 % thickness reductions. Microstructural examination of the received sample revealed a non-uniform coarse grain structure with precipitates of oxide phases rich in niobium and Laves. These precipitates are shredded and randomly distributed in the microstructure with elongated grains after hot-rolling under 84 % reduction. Following the solution-treatment, this sample's simultaneous static recrystallization and precipitation of secondary-phase particles has formed a banded structure of grain-size and secondary-phase particle bands. The particles of the secondary-phases are locally accumulated on the material's surface in the 96 % hot-rolled sample, creating a duplex grain and non-random microstructures with different cross-sectional conditions. The secondary-phase particle bands caused by the previous solution-treatment are retained in the pre-hot-rolled sample under 84 % reduction after aging. Furthermore, XRD analysis results show that the precipitation peak of γ'/γ phase was more visible and intense in this sample. Tensile tests conducted at room temperature and 649 °C indicate that the pre-hot-rolled sample with an 84 % reduction exhibited a 1 % improvement in cold ductility and an 8 % enhancement in hot ductility compared to the sample with a 96 % reduction.

Multiple DNA cycle amplification for highly efficient detection of mercury pollution in food.

Mercury ion (Hg2+), a highly toxic metal pollutant, is widely found in the environment and can enter the human body through the food chain, causing various health issues. Sensitive and accurate methods for monitoring Hg2+ are highly desirable for ensuring food safety. Herein, we propose a self-sustainable multiple amplification system (MAS) for Hg2+ determination through the reciprocal activation between catalytic hairpin assembly (CHA) and rolling circle amplification (RCA). The thymine-encoded recognition element specifically recognizes Hg2+, triggering the exposure of the initiator. The initiator then motivates the mutual activation of CHA and RCA to accelerate the production of an exponentially amplified signal. The MAS method achieved a low detection limit of 11 pM. Due to its reliable target recognition and robust amplification efficiency, the MAS circuit facilitated the highly efficient and accurate analysis of low-abundance Hg2+ in milk and snakehead samples, thus providing a potentially new tool for food safety control.

Hybrid chain reaction nanoscaffold-based functional nucleic acid nanomaterial cascaded with rolling circle amplification for signal enhanced miRNA let-7a detection.

A novel functional nucleic acid (FNA) nanomaterial based on hybrid chain reaction (HCR) nanoscaffolds is proposed to solve the problem of time superposition and repeated primer design in sensitive miRND detection using cascade amplification technique. Rolling circle amplification (RCA) was cascaded with the prepared FNA nanomaterials for miRNA let-7a (as a model target) sensitive detection by lateral flow assay (LFA). Under the optimal conditions, the proposed RCA-FNA-LFA assay demonstrated the specificity and accuracy for miRNA let-7a detection with a detection limit of 1.07 pM, which increased sensitivity by nearly 20 times compared with that of RCA -LFA assay. It is worth noting that the non-target-dependent self-assembly process of HCR nanoscaffolds does not take up the whole detection time, thus, less time is taken than that of the conventional cascaded method. Moreover, the proposed assay does not need to consider the system compatibility between two kinds of isothermal amplification techniques. As for detection of different miRNAs, only the homologous arm of the padlock probe of RCA needs to be changed, while the FNA nanomaterial does not need any change, which greatly simplifies the primer design of the cascaded amplification techniques. With further development, the proposed RCA-FNA-LFA assay might achieve more sensitive and faster results to better satisfy the requirements of clinical diagnosis combing with more sensitive labels or small strip reader.

A novel deep learning framework for rolling bearing fault diagnosis enhancement using VAE-augmented CNN model.

In the context of burgeoning industrial advancement, there is an increasing trend towards the integration of intelligence and precision in mechanical equipment. Central to the functionality of such equipment is the rolling bearing, whose operational integrity significantly impacts the overall performance of the machinery. This underscores the imperative for reliable fault diagnosis mechanisms in the continuous monitoring of rolling bearing conditions within industrial production environments. Vibration signals are primarily used for fault diagnosis in mechanical equipment because they provide comprehensive information about the equipment's condition. However, fault data often contain high noise levels, high-frequency variations, and irregularities, along with a significant amount of redundant information, like duplication, overlap, and unnecessary information during signal transmission. These characteristics present considerable challenges for effective fault feature extraction and diagnosis, reducing the accuracy and reliability of traditional fault detection methods. This research introduces an innovative fault diagnosis methodology for rolling bearings using deep convolutional neural networks (CNNs) enhanced with variational autoencoders (VAEs). This deep learning approach aims to precisely identify and classify faults by extracting detailed vibration signal features. The VAE enhances noise robustness, while the CNN improves signal data expressiveness, addressing issues like gradient vanishing and explosion. The model employs the reparameterization trick for unsupervised learning of latent features and further trains with the CNN. The system incorporates adaptive threshold methods, the "3/5" strategy, and Dropout methods. The diagnosis accuracy of the VAE-CNN model for different fault types at different rotational speeds typically reaches more than 90 %, and it achieves a generally acceptable diagnosis result. Meanwhile, the VAE-CNN augmented fault diagnosis model, after experimental validation in various dimensions, can achieve more satisfactory diagnosis results for various fault types compared to several representative deep neural network models without VAE augmentation, significantly improving the accuracy and robustness of rolling bearing fault diagnosis.

Aptamer-Loop DNA Nanoflower Recognition and Multicolor Fluorescent Carbon Quantum Dots Labeling System for Multitarget Living Cell Imaging.

Visualization of multiple targets in living cells is important for understanding complex biological processes, but it still faces difficulties, such as complex operation, difficulty in multiplexing, and expensive equipment. Here, we developed a nanoplatform integrating a nucleic acid aptamer and DNA nanotechnology for living cell imaging. Aptamer-based recognition probes (RPs) were synthesized through rolling circle amplification, which were further self-assembled into DNA nanoflowers encapsulated by an aptamer loop. The signal probes (SPs) were obtained by conjugation of multicolor emission carbon quantum dots with oligonucleotides complementary to RPs. Through base pairing, RPs and SPs were hybridized to generate aptamer sgc8-, AS1411-, and Apt-based imaging systems. They were used for individual/simultaneous imaging of cellular membrane protein PTK7, nucleolin, and adenosine triphosphate (ATP) molecules. Fluorescence imaging and intensity analysis showed that the living cell imaging system can not only specifically recognize and efficiently bind their respective targets but also provide a 5-10-fold signal amplification. Cell-cycle-dependent distribution of nucleolin and concentration-dependent fluorescence intensity of ATP demonstrated the utility of the system for tracking changes in cellular status. Overall, this system shows the potential to be a simple, low-cost, highly selective, and sensitive living cell imaging platform.

Multispectral pathogens detection in food using multiplex hyperbranched saltatory rolling circle amplification.

Foodborne illnesses caused by Salmonella and Staphylococcus aureus are a significant public health concern, leading to societal and economic repercussions. It is important to develop a simple and straightforward bacteria detection and identification method. A triple-probe multiplex rolling circle amplification technique has been developed to simultaneously detect Salmonella Typhimurium and S. aureus. This method utilizes fluorophore-labeled long padlock probes targeting S. Typhimurium invA and S. aureus glnA specific genes, along with a pH-based detection approach for direct visual identification. The multiplex hyperbranched saltatory rolling circle amplification assay at 30 °C has showed promising results with synthetic targets within 30 min and real bacteria within 2 h after establishing the detection settings. The assay is specific for S. aureus and S. Typhimurium, with a limit of detection of 39 µM for fluorescence and 78 µM for colorimetric. In the simulative test of this method for the detection of S. Typhimurium and S. aureus in milk, the limit of detection for the fluorescence signal after 2 h of amplification was 10 CFU/mL and 5 CFU/mL, respectively. The detection method was evaluated to be stable enough to detect pathogen for 3.29 months. Consequently, this triple-probe-multiplex rolling circle amplification method displays notable specificity, sensitivity, as well as ease of interpretation when testing food samples for harmful pathogens.

Refined composite multiscale slope entropy and its application in rolling bearing fault diagnosis.

Rolling bearing is the key component of rotating machinery, and its vibration signal usually exhibits nonlinear and nonstationary characteristics when failure occurs. Multiscale permutation entropy (MPE) is an effective nonlinear dynamics analysis tool, which has been successfully applied to rolling bearing fault diagnosis in recent years. However, MPE ignores the deep amplitude information when measuring the complexity of the time series and the original multiscale coarse-graining is insufficient, which requires further research and improvement. In order to protect the integrity of information structure, a novel nonlinear dynamic analysis method termed refined composite multiscale slope entropy (RCMSlE) is proposed in this paper, which introduced the concept of refined composite to further boost the performance of MPE in nonlinear dynamical complexity analysis. Furthermore, RCMSlE utilizes a novel symbolic representation that takes full account of mode and amplitude information, which overcomes the weaknesses in describing the complexity and regularity of bearing signals. Based on this, a GWO-SVM multi-classifier is introduced to fulfill mode recognition, and then a new intelligent fault diagnosis method for rolling bearing based on RCMSlE and GWO-SVM is proposed. The experimental results show that the proposed method can not only accurately identify different fault types and degrees of rolling bearing, but also has a short computation time and better performance than other comparative methods.

Leaf rolling detection in maize under complex environments using an improved deep learning method.

Leaf rolling is a common adaptive response that plants have evolved to counteract the detrimental effects of various environmental stresses. Gaining insight into the mechanisms underlying leaf rolling alterations presents researchers with a unique opportunity to enhance stress tolerance in crops exhibiting leaf rolling, such as maize. In order to achieve a more profound understanding of leaf rolling, it is imperative to ascertain the occurrence and extent of this phenotype. While traditional manual leaf rolling detection is slow and laborious, research into high-throughput methods for detecting leaf rolling within our investigation scope remains limited. In this study, we present an approach for detecting leaf rolling in maize using the YOLOv8 model. Our method, LRD-YOLO, integrates two significant improvements: a Convolutional Block Attention Module to augment feature extraction capabilities, and a Deformable ConvNets v2 to enhance adaptability to changes in target shape and scale. Through experiments on a dataset encompassing severe occlusion, variations in leaf scale and shape, and complex background scenarios, our approach achieves an impressive mean average precision of 81.6%, surpassing current state-of-the-art methods. Furthermore, the LRD-YOLO model demands only 8.0 G floating point operations and the parameters of 3.48 M. We have proposed an innovative method for leaf rolling detection in maize, and experimental outcomes showcase the efficacy of LRD-YOLO in precisely detecting leaf rolling in complex scenarios while maintaining real-time inference speed.

Functionalized primer initiated signal cycles and personal glucose meter for sensitive and portable miRNA analysis.

MicroRNA (miRNA) has garnered considerable attention due to its diagnostic capabilities, such as in hypoxic cognitive impairment and cancers. However, the existing miRNA detection methods are commonly criticized for the drawbacks of low sensitivity and false-positive detection derived from interfering molecules. Here, we provide a novel, sensitive and portable method for miRNA detection by combining target identification based cyclization of padlocks, immobilized primer-based signal amplification and a personal glucose meter. The proposed method exhibits several advantages, including precise identification of specific sites, exceptional sensitivity and instrument-free feature. These attributes hold great promise for the diagnosis and clinical investigation of various diseases, such as cancer and hypoxic cognitive impairment, enabling a deeper understanding of their pathological and physiological aspects.

With miRNA-155 as detective target, the feasibility of the method has been demonstrated. The padlock sequences are cyclized by miRNA-155, which subsequently hybridize with primer sequence that is immobilized on the surface of a 96-well plate, and the interfering molecules are removed. This DNA polymerase triggers a chain extension process on the terminus of primer sequence, activating DNAzyme based cleavage. Consequently, a multitude of linker sequences are generated to facilitate the formation of the 'e/linker/f/sucrase' on magnetic bead, thereby enabling the catalysis of sucrose into glucose. This enzymatic reaction may be identified and measured using the personal glucose meter.

Research on Microstructure, Mechanical Properties, and High-Temperature Stability of Hot-Rolled Tungsten Hafnium Alloy.

W-(0, 0.1, 0.3, 0.5) wt.% Hf (mass fraction, wt.%) materials were fabricated by the powder metallurgy method and hot rolling. The microstructure, mechanical properties, and high-temperature stability of alloys with varying compositions were systematically studied. The active element Hf can react with the impurity O segregated at the grain boundary to form fine dispersed HfO2 particles, refining the grains and purifies and strengthening the grain boundary. The average size of the sub-grains in the W-0.3 wt.% Hf alloy is 4.32 µm, and the number density of the in situ-formed second phase is 6.4 × 1017 m-3. The W-0.3 wt.% Hf alloy has excellent mechanical properties in all compositions of alloys. The ultimate tensile strength (UTS) is 1048 ± 17.02 MPa at 100 °C, the ductile fracture occurs at 150 °C, and the total elongation (TE) is 5.91 ± 0.41%. The UTS of the tensile test at 500 °C is 614 ± 7.55 MPa, and the elongation is as high as 43.77 ± 1.54%. However, more Hf addition will increase the size of the second-phase particles and reduce the number density of the second-phase particles, resulting in a decrease in the mechanical properties of the tungsten alloy. The isochronal annealing test shows that the recrystallization temperature of W-Hf alloy is 1400 °C, which is 200 °C higher than rolling pure tungsten.

Fatigue Strength Improvement of Laser-Directed Energy Deposition 316L Stainless Steel with In Situ Ultrasonic Rolling by Preliminary Investigation.

In this study, to improve the fatigue strength of the LDED (laser-directed energy deposition) 316L stainless steel, an in situ ultrasonic rolling technology is developed to assist the laser-directed energy deposition process (LDED-UR). The microstructural characteristics and fatigue behavior are comprehensively discussed. The results show that the average size of pores of the LDED-UR alloy is about 10.2 µm, which is much smaller than that of the LDED alloy (34.1 µm). Meanwhile, the density of the LDED alloy is also enhanced from 98.26% to 99.27% via the in situ ultrasonic rolling. With the application of the in situ ultrasonic rolling, the grains are transformed into fully equiaxed grains, and their average grain size is greatly reduced from 84.56 µm to 26.93 µm. The fatigue limit of the LDED-UR alloy is increased by 29% from 210 MPa (LDED alloy) to 270 MPa, which can be ascribed to the decreased porosity and the fine grains. In particular, the crack initiation site of the LDED alloy is located at the surfaces, while it is nucleated from the sub-surface for the LDED-UR alloy. This is mainly attributed to the compression residual stress induced by the in situ ultrasonic rolling. This research offers a valuable understanding of the failure mechanisms in additively manufactured metals, guiding the development of effective strategies to improve their fatigue threshold under severe operating conditions.

Crystal Plasticity Finite Element Simulation of Grain Evolution Behavior in Aluminum Alloy Rolling.

In this study, the crystal plasticity finite element method was established by coupling the crystal plasticity and finite element method (FEM). The effect of rolling deformation and slip system of polycrystalline Al-Mg-Si aluminum alloy was investigated. The results showed that there was a pronounced heterogeneity in the stress and strain distribution of the material during cold rolling. The maximum strain and shear strain occurred at surface of the material. The smaller the grain size, the lower the strain concentration at the grain boundary. Meanwhile, a smaller strain difference existed between the grain interior and near the boundary. The rotation of grains leads to significant differences in deformation and rotation depending on their initial orientations during the rolling process. The slip system of (11-1)<-110> had a large effect on the plastic deformation, (111)<10-1> is second, and the effect of (1-11)<011> slip system on the plastic deformation is the smallest. After deformation, the grain orientation concentration was increased with deformation. Therefore, both the strength and volume fraction of texture were increased with the increase in rolling deformation. The experimental results of EBSD indicated that the large rolling reduction resulted in severe grain twisting, so the texture strength was increased. The simulation results were in close agreement with the experimental results. This study provides a theoretical basis for the rolling process, microstructure, and performance control of aluminum alloys.

Study on Mechanical and Electrical Properties of High Content CNTs/Cu Composites.

It is expected that composites made of carbon nanotubes (CNT) and copper (Cu) display both mechanical and electrical properties, but the low damage dispersion and high-quality composite of high-content CNTs have always been research difficulties. In this paper, high-content CNTs/Cu composites were prepared. The effects of the sintering method, sintering temperature, directional rolling and the CNTs' content on the relative density, hardness and electrical conductivity of the composites were studied. The uniform dispersion of high-content CNTs in Cu matrix was achieved by ball milling, sintering and rolling, and the processes did not cause more damage to the CNTs. The properties of composites prepared by spark plasma sintering (SPS) and vacuum hot pressing sintering (HPS) were compared, and the optimum process parameters of SPS were determined. When the CNTs' content is 2 wt.%, the hardness is 134.9 HBW, which is still 2.3 times that of pure Cu, and the conductivity is the highest, reaching 78.4%IACS. This study provides an important reference for the high-quality preparation and performance evaluation of high-content CNTs/Cu composites.

Understanding the leaf rolling of paddy and exploring its management options under aerobic rice.

Rice is a staple food in the diets of more than half of the world's population. With India's irregular rainfall patterns and continual environmental anomalies, particularly in Kerala, the identification of climate-smart management practices which can withstand drought is critical. In this context, atrial was conducted in the experimental plots to evolve effective water and nutrient management practices under aerobic rice in lateritic soils of Kerala. However, during the experiment in a few treatments, rolling of leaves was observed, and when explored for the reasons, it was due to soil moisture deficit and plant water stress. When compared to other crop species, rice is highly vulnerable to water deficit. In this regard, an attempt has been made to study the leaf rolling pattern in aerobic rice and how this can be managed with a few soil amendments so that rice productivity can be sustained. The results showed that plant growth parameters, relative water content (RWC), membrane leakage (ML) and spectral signatures were significantly affected by the leaf rolling. It was found that leaf rolling affected plants have less RWC and higher ML and are under drought stress. Pearson correlation analysis showed a strong positive correlation (P < 0.05) of key spectral indices with other physiological traits such as RWC and negatively correlated with ML. Moisture absorbent media such as cocopeat, compost, saw dust and vermiculite were attempted as management strategies to overcome this stress. Results showed that among the absorbents attmepted, cocopeat was found to be better in managing the stress. These results suggest that for aerobic rice under lateritic soil, moisture absorbent media such as cocopeat, has to be incorporated so that it can reduce the rate of leaf rolling thereby sustaining the paddy yield.

Impact of Healthy Lifestyle Factors on Life Expectancy and Lifetime Health Care Expenditure: Nationwide Cohort Study.

BACKGROUND: The association between lifestyle risk factors and the risk of mortality and chronic diseases has been established, while limited research has explored the impact of healthy lifestyle factors on lifetime health care expenditure using longitudinal individual data. OBJECTIVE: We aimed to determine the individual and combined effects of 5 healthy lifestyle factors on life expectancy and lifetime health care expenditure in Taiwan. METHODS: Using data from the National Health Interview Survey cohort, 5 healthy lifestyle behaviors were defined and analyzed: nonsmoking, avoiding excessive alcohol consumption, engaging in sufficient physical activity, ensuring sufficient fruit and vegetable intake, and maintaining a normal weight. We used a rolling extrapolation algorithm that incorporated inverse probability of treatment weighting to estimate the life expectancy and lifetime health care expenditure of the study populations with and without healthy lifestyle factors. RESULTS: A total of 19,893 participants aged ≥30 (mean age 48.8, SD 13.4) years were included, with 3815 deaths recorded during a median follow-up period of 15.6 years. The life expectancy and per capita estimated lifetime health care expenditures for the overall study population were 35.32 years and US $58,560, respectively. Multivariable-adjusted hazard ratios for all-cause mortality in participants adhering to all 5 healthy lifestyle factors, compared with those adhering to none, were 0.37 (95% CI 0.27-0.49). We found significant increases in life expectancy for nonsmokers (2.31 years; 95% CI 0.04-5.13; P=.03), those with sufficient physical activity (1.85 years; 95% CI 0.25-4.34; P=.02), and those with adequate fruit and vegetable intake (3.25 years; 95% CI 1.29-6.81; P=.01). In addition, nonsmokers experienced a significant reduction in annual health care expenditure (-9.78%; 95% CI -46.53% to -1.45%; P=.03), as did individuals maintaining optimal body weight (-18.36%; 95% CI -29.66% to -8.57%; P=.01). Overall, participants adhering to all 5 healthy lifestyle behaviors exhibited a life gain of 7.13 years (95% CI 1.33-11.11; P=.02) compared with those adhering to one or none, with a life expectancy of 29.19 years (95% CI 25.45-33.62). Furthermore, individuals adopting all 5 healthy lifestyle factors experienced an average annual health care expenditure reduction of 28.12% (95% CI 4.43%-57.61%; P=.02) compared with those adopting one or none. CONCLUSIONS: Adopting a healthy lifestyle is associated with a longer life expectancy and a reduction of health care expenditure in Taiwanese adults. This contributes to a more comprehensive understanding of the impact of healthy lifestyle factors on the overall health and economic burden.

Widely targeted metabolomic analysis reveals metabolite changes induced by incorporating black tea fermentation techniques in oolong tea processing for quality improvement.

Oolong tea, a semi-fermented tea, has a prominent fruity and floral aroma, resembling green tea's astringency and pungency but lacking black tea's mellowness. Oolong tea incorporating black tea fermentation techniques (OT-IBTFT) not only retained its excellent floral and fruity aroma but also reduced astringency and enriched taste. However, metabolite changes remain unknown. In this study, widely targeted metabolomic analysis showed OT-IBTFT reduced prunin, gallocatechin, methyl gallate, and increased loliolide by changing the flavonoid biosynthesis and biosynthesis of secondary metabolites pathways, thereby reducing the astringency and increasing the mellow taste and richness to improve oolong tea quality. In addition, Wrap-rolling 5 times increased fermentation, improving the color and aroma of oolong tea by increasing theaflavic acid and 2-furoic acid, is more significant than wrap-rolling once. In conclusion, these findings provide a theoretical basis for the improvement of oolong tea processing techniques and flavor and quality control.

Ultra-sensitive detection of SARS-CoV-2 S1 protein by coupling rolling circle amplification with poly(N-isopropylacrylamide)-based sandwich-type assay.

In the past few years, the COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) seriously threatens global public health security due to its high contagiousness. It remains of vital importance to develop a rapid and sensitive assay for SARS-CoV-2. In this work, we proposed a sandwich-type assay based on poly(N-isopropylacrylamide) (PNIPAM), allowing efficient detection of the SARS-CoV-2 S1 protein in the homogeneous solution. Firstly, a direct sandwich-type assay was established with a linear range of 0.2-2 µg/mL and a limit of detection (LOD) of 0.11 µg/mL, which could realize rapid detection in about 1 h. Furthermore, the sandwich-type assay coupled with rolling circle amplification (RCA) obtained an increase in sensitivity of 5.9 × 104 folds with a wide linear range of 0.01 - 100 ng/mL and a LOD of 1.88 pg/mL. The average recoveries in unpretreated saliva were 90 %-113.0 %, indicating the potential of the developed method for application in practical samples. Given the high selectivity and sensitivity of the developed method, it has a significant potential for rapid and early detection of SARS-CoV-2.