9results about How to "Low background" patented technology

This invention relates to the field of biomedical detection technology, and discloses a bitetrahedral framework nucleic acid TDN cascade amplification system and its application, including TDN-1 and TDN-2. TDN-1 has a hairpin H1 containing a fluorescent reporter group attached to its surface, and TDN-2 has a hairpin H2 attached to its surface. The sequences of H1 and H2 are designed to undergo an alternating hybridization chain reaction triggered by target mRNA. This scheme relies on the synergistic effect of TDN structural anchoring and precise hairpin probe sequence design to overcome the technical defects of traditional free HCR hairpins in living cells, such as poor stability, low reaction efficiency, and non-specific triggering, achieving more efficient and specific intracellular signal amplification. Furthermore, it enables highly specific and sensitive in-situ imaging and dynamic tracking of low-abundance mRNAs such as c-Myc in single living cells, effectively solving the problems of insufficient detection sensitivity and false positives caused by the inability of traditional detection methods to effectively enrich targets and the low efficiency and high background of traditional HCR and other signal amplification technologies in intracellular applications.

The invention relates to a fluorescence and colorimetric dual-mode biosensing method for detecting caffeine and application thereof, the method causes CRISPR / Cas13a to regulate and control Fe-MOFs to fall off from a signal probe based on to-be-detected liquids with different concentration gradients, the fallen Fe-MOFs collapses under the action of sodium pyrophosphate to release 2-aminoterephthalic acid and ferric ions, and the 2-aminoterephthalic acid and ferric ions are subjected to fluorescence and colorimetric dual-mode biosensing method is used for detecting caffeine. 2-aminoterephthalic acid is converted into a fluorescence signal, meanwhile, Prussian blue generated by reaction of ferric ions and potassium ferrocyanide is converted into a colorimetric signal, and a fluorescence and colorimetric dual-mode biosensing method is constructed; according to the sensor, interference factors can be effectively eliminated by outputting two detection signals and performing cross validation; the advantages of high sensitivity and wide linear range of a fluorescence method and the advantages of simple operation and visual result of a colorimetric method are combined, so that a target object can be accurately recognized, the lower detection limit can be reduced, and the accuracy of a quantitative result can be ensured; according to the sensing method, visual observation can be achieved, precise instruments are not needed, and good application value is achieved.

The present application provides a kit and method for detecting RNA at room temperature. The kit for detecting RNA at room temperature comprises: a target RNA recognition and amplification component and a double signal amplification component, and the further amplification and reporting of the signal are completed by coupling the two components, and the high-sensitivity detection of RNA is realized. The method for detecting RNA at room temperature of the present application does not need a complex reverse transcription process, can reduce the complexity of the reaction and the cost of the instrument, and has high detection efficiency.

The application provides a method for separating and purifying cell surface proteins and application thereof. The method comprises the following steps: culturing cells to be separated, adding an azide solution to the cells for incubation, then adding a Tris-HCl buffer to terminate the reaction, so as to label the cell surface proteins with azides; then adding a TNTE buffer and a protease inhibitor to lyse the cells, centrifuging to obtain cell lysates labeled with azides; incubating the cell lysates labeled with azides with phosphine-biotin-streptavidin magnetic beads, so as to enrich the cell surface proteins labeled with azides, and obtain magnetic beads containing the cell surface proteins. The method can effectively separate the cell surface proteins, has low background, high efficiency and good repeatability, and can be applied to quantitative analysis of cell surface proteomes.

The application discloses an RNA-protein complex, an expression vector, a kit and application thereof. The RNA-protein complex comprises: a chimeric RNA having a molecular structure represented as N1-N2 or N2-N1; wherein N1 is a target RNA sequence, and N2 is an RNA aptamer configured to activate a fluorophore molecule to emit spectral fluorescence; and a recombinant fusion protein having a molecular structure represented as P1-P2 or P2-P1; wherein P1 is a target protein, and P2 is a fluorescent protein, and the target protein recognizes and binds to the target RNA sequence.

The invention relates to the technical field of lead ion detection, in particular to a lead ion detection colorimetric sensor and application thereof.The lead ion detection colorimetric sensor comprises hemin, a substrate chain S, an enzyme chain Dz and a DNA chain DS with three palindromic structures; in the absence of Pb < 2 + >, the substrate chain S and the enzyme chain Dz are hybridized to form a stable S-Dz double chain; when Pb is introduced, an enzyme chain Dz can be activated, and lead ions are specifically recognized and used as cofactors. Through an annealing process, the DNA chain DS is subjected to intramolecular hybridization and self-folding so as to be self-assembled into a definitely-defined and monodisperse DNA nanosphere; the substrate chain S and the enzyme chain Dz can be hybridized to form a stable S-Dz double chain; a plurality of S-Dz are concentrated on a limited nanosphere surface (DS-S-Dz), the catalysis direction is optimized, side reactions are reduced, and a signal DNAzyme can be quickly formed, so that a color signal is remarkably amplified, and lead ion detection with higher sensitivity, lower background and higher stability is realized.

This invention discloses a detection method for ultrasensitive fluorescence counting immunoassay using bioorthogonal reaction-immobilized bacteria, comprising the following steps: (1) transforming recombinant plasmids into *E. coli*, and inducing transcription into the T promoter using IPTG to induce *E. coli* to express green fluorescent protein; (2) dissociating Cu-MOF nanoparticles with ascorbic acid, allowing the azide groups of *E. coli* modified with azidoform to bind to the alkyne groups on alkyne-modified bovine serum albumin, thus immobilizing *E. coli* on a well plate; (3) amplifying the signal through the self-replication of luminescent *E. coli*, converting the concentration of the biomarker into fluorescent bright spots of fluorescent *E. coli*, thereby achieving quantitative detection. This invention has strong detection specificity, good stability and accuracy, and a detection limit lower than the clinical gold standard ELISA, allowing for visual detection of biomarker concentrations.

The present disclosure relates to a knee joint lesion detection method and device, an electronic device and a storage medium, and relates to the technical field of knee joint lesion detection. The method comprises: performing similarity information calculation on a T1 first image and a T2 second image in an acquired knee image, and obtaining a corresponding third image based on the similarity information; synthesizing the T1 first image, the T2 second image and the third image to obtain a to-be-processed image; and performing knee joint lesion detection on the to-be-processed image based on a preset target detection model. The present disclosure can realize knee joint lesion detection.

The application discloses a kind of network construction methods for extracting space-time features of dynamic gesture RGB video frame, belong to computer vision and deep learning field.Aiming at the problems that existing network weakly resists blur, hand small target extraction effect is poor, gesture frame offset and time sequence redundancy influence training precision, the application constructs single mode space-time feature extraction network based on ShuffleNetV2-GRU.Spatial branch adds learnable gaussian blur branch, adopts SPDConv optimization down sampling, Stage4 layer is replaced by lightweight DCNv2 to extract hand irregular features, and multi-scale feature fusion is completed by WAFF-ASFF.The time sequence branch accesses TAM module between spatial network and GRU to correct frame offset, and relies on adjacent frame weighting module to strengthen key time sequence information.Preprocessing distinguishes trajectory, gesture posture and makes differential enhancement, and combines hand ROI to optimize input data.The application has excellent extraction precision, model lightweight, inference is fast, and is suitable for embedded device deployment.