10results about How to "Reduce screening costs" patented technology

The invention discloses a haplotype molecular marker related to cotton fiber strength and application of a detection primer of the haplotype molecular marker, and relates to the technical field of plant molecular biology and genetic breeding. The haplotype molecular marker is located in 112, 985, 431-112, 990 and 059bp regions of A06 chromosome of a cotton reference genome, a haplotype block is formed by nine closely linked SNP (Single Nucleotide Polymorphism) sites, the incidence relation between three haplotypes Hap1, Hap2 and Hap3 in the block and fiber strength is defined, and a new molecular target is provided for cotton fiber quality breeding. Compared with a single SNP marker, the haplotype molecular marker provided by the invention has higher stability and phenotype prediction accuracy under a complex genetic background. Genetic typing can be carried out in the cotton seedling stage based on the marker, fiber maturation does not need to be waited, the breeding period is greatly shortened, and the field screening cost is reduced.

The invention relates to a diagnosis and treatment data management and collaborative diagnosis and treatment method for diabetic retinopathy, which is applied to a medical care terminal, and comprises the following steps: in response to successful login of a user, displaying a homepage of the medical care terminal; skipping to a medical record auditing page under the condition that the user identity is a medical worker and a request for viewing the medical record auditing page is received; the medical record auditing page is used for displaying the medical record data with the marked auditing state; the medical record data is uploaded by a patient end, detection equipment and / or a hospital information system; when a selection operation on the target medical record data whose auditing state is to be audited is received, displaying the target medical record data in response to a preview operation triggered through a preview component; and when a selection operation on the auditing passing component is received, updating the auditing state of the target medical record data to be auditing passing. Therefore, by means of unified state marking and medical record data summarization, medical record state chaos caused by operation habit differences is reduced, and the problems that medical data are scattered and difficult to integrate are solved.

The application discloses a kind of temperature-resistant water-soluble monomer design methods based on generative artificial intelligence.The method comprises the following steps: constructing polymer thermal performance dataset, training quantitative structure-property relationship prediction model;Adopt generative artificial intelligence strategy, by the structure deconstruction and recombination of existing temperature-resistant monomer and water-soluble monomer, generate massive virtual monomer library;Build water-soluble evaluation index considering solubility parameter, oil-water partition coefficient and hydrogen bond number;Combined with synthesis accessibility score, multi-objective high-throughput screening is carried out on virtual monomer library.The application realizes the synergistic optimization and high-throughput screening of the temperature resistance and water solubility of candidate monomers, solves the problems of limited types of existing temperature-resistant water-soluble monomers, mainly relying on experience trial and error in research and development, and low screening efficiency, especially the lack of unified and calculable evaluation index for water solubility, which makes it difficult to optimize and screen the temperature resistance and water solubility as constraints in the process of artificial intelligence aided design.

The application provides a method for rapidly screening aptamers based on exonuclease degradation rate, a reaction system with added aptamers and targets, and a control system with only added aptamers, after adding exonuclease, part of samples are taken out every certain time and added into a quenching solution containing a fluorescent dye, the fluorescent intensity is detected and the relative fluorescent intensity of the reaction system and the control system is compared, and the binding capacity of the aptamers and the targets is indirectly represented. The application can qualitatively detect the affinity of multiple groups of aptamers in a high-throughput and large-batch manner, greatly shortens the screening period, reduces the cost, and is beneficial to subsequent quantitative detection.

This invention relates to the field of biomedical detection technology, specifically to plasma circulating microbial biomarkers for early screening of gastric cancer and their applications. The plasma circulating microbial biomarkers include: *Ralstonia solanacearum*, *Staphylococcus aureus*, *Alternaria metachromatica*, *Porphyromonas gingivalis*, *Lactobacillus reuteri*, *Rhodococcus erythropolis*, *Akkermansia muciniphila*, *Lactobacillus gasseri*, *Bifidobacterium bifidum*, and *Neisseria gonorrhoeae*. This invention screens and, for the first time, combines 10 specific microbial biomarkers with Low Pass technology. WGS technology can achieve detection results at low depths, significantly reducing screening costs while ensuring detection sensitivity, and providing a brand-new solution for early gastric cancer screening.

The application discloses a blood pressure reducing dipeptide activity prediction method based on XGBoost, and belongs to the fields of food science and biology technology. The method comprises the following steps: firstly, collecting published blood pressure reducing dipeptide sequences and their activity IC 50 values, and constructing a data set; secondly, introducing sequence, physicochemical and amino acid atomic composition features of a peptide segment, and performing feature expression on the dipeptide sequence; thirdly, performing principal component expression on the features of the peptide segment, and performing principal component selection; fourthly, combining the principal components and an XGBoost regression model to construct a prediction model and performing precision evaluation on the model; then, training the model by using all data of an existing dipeptide data set, and realizing model construction; and finally, applying the prediction model to perform activity prediction on unknown blood pressure reducing dipeptide sequences. The prediction method can reduce the complexity of peptide activity prediction, effectively improve the prediction precision, reduce the screening cost, and can be widely applied to blood pressure reducing activity and other activity prediction of dipeptide sequences.

This invention provides an AI-based multi-model collaborative intelligent screening and deep analysis method for multimodal data, comprising: differential preprocessing based on modal differences in multimodal samples, dynamically adjusting preprocessing parameters through sample metadata analysis; evaluating sample data quality using multi-dimensional indicators to obtain high-value data; using an importance and diversity coupled optimization strategy to screen high-value data to obtain effective samples; performing modal alignment on the screened samples to complete cross-modal feature fusion and generate a unified fused feature vector; performing multi-dimensional deep analysis on the fused feature vector to mine inter-modal correlation information, and combining domain transfer learning to achieve result generalization; evaluating the analysis results in real time based on preset indicators, and dynamically adjusting the core parameters of the entire process based on the evaluation results. The beneficial effects of this invention are: solving the problems of high screening cost, low accuracy, poor fusion effect, weak analytical capability, poor interpretability, and inflexible deployment in existing technologies.

This invention discloses a method and system for recommending bank points malls based on multi-dimensional user data analysis. The method constructs an intelligent recommendation closed loop through a six-step core process: First, it organizes users' regular consumption data, achieving multi-dimensional collection, cleaning, labeling, and dynamic updates; second, it collects and filters spatiotemporal hotspot data of the user's region to accurately match offline scenario needs; third, it integrates multi-channel online hotspot data, quantifying popularity and timeliness; fourth, it binds the two types of hotspot data with points mall products by weight; fifth, it calculates and dynamically adjusts the correlation between products; and finally, it generates a default recommendation list based on the hotspot correlation and dynamically switches to related product recommendations based on real-time user interaction behavior. This invention solves the problems of single recommendation dimensions, insufficient accuracy, and delayed timeliness in existing technologies. By integrating multi-dimensional data and a dynamic feedback mechanism, it significantly improves the accuracy of points mall recommendations, user interaction experience, and points redemption conversion rate.

The invention relates to the technical field of tobacco agriculture, in particular to a method for screening tobacco varieties with high flavonoid content based on Multiplex 3, and the Multiplex 3 is used for detecting the flavonoid content of tobacco leaves, so that the tobacco varieties with the tobacco leaves with high flavonoid content are screened. The screening method provided by the invention can accurately, losslessly and quickly identify the tobacco single plants with the tobacco leaves with high flavonoid content, and compared with the prior art, the method provided by the invention has the advantages of simplicity and quickness in detection, accuracy, losslessness, low destructiveness, no application scene limitation, safety and reliability.

This invention relates to the field of agricultural breeding technology, specifically to a method for screening nitrogen-efficient rice mutants. The method includes: providing a rice mutant population subjected to space-induced mutagenesis; subjecting the rice mutant population to hydroponic stress treatment with chlorate solution before the three-leaf stage; measuring the seedling length of the treated group and the control group, and calculating the seedling length inhibition rate; and screening nitrogen-efficient candidate mutants based on the seedling length inhibition rate. This invention also relates to nitrogen-efficient rice mutants obtained by the method and their application in nitrogen-efficient rice breeding. The method of this invention is simple to operate, has a short cycle time, and low cost, enabling rapid and accurate screening of nitrogen-efficient materials from large-scale populations, which is of great significance for cultivating new crop varieties with efficient nitrogen fertilizer utilization.