32 results about "Pregnancy outcomes" patented technology

The invention discloses a method and a system for predicting preeclampsia risk of a pregnant woman based on computer implementation. The method integrates the concentration level of vitamin D (especially 25-hydroxyvitamin D) in serum of pregnant women, angiogenesis biomarkers (such as sFlt-1 / PlGF ratio), conventional clinical indexes (such as mean arterial pressure and body mass index) and personal medical history data. A machine learning algorithm (such as a random forest or a gradient lifting model) is adopted to carry out weighted analysis on the multi-dimensional data, and a dynamic and high-precision prediction model is constructed. The system comprises a data acquisition module, an intelligent prediction module and a clinical decision support module, and can provide real-time risk assessment and personalized intervention suggestions (such as a vitamin D supplement scheme) for medical staff, so that early warning and effective management of preeclampsia are realized, and the risk of pregnancy outcome caused by maternal and infant poor pregnancy is reduced.

The invention relates to the field of biomarkers, and particularly provides a polycystic ovarian syndrome pregnancy outcome diagnosis marker and application thereof. According to the present invention, the endometrial targeting metabonomics research is adopted to screen the disease-related potential metabolic markers such as N-Acetylaspartic acid, Suberic acid and isoallolithocholic acid, and the three metabolites are subjected to quantitative detection so as to accurately predict the pregnancy outcome of the polycystic ovarian syndrome patient, such that the pregnancy outcome of the polycystic ovarian syndrome patient can be accurately predicted, and the prediction of the pregnancy outcome of the polycystic ovarian syndrome patient can be easily achieved, such that the disease-related potential metabolic markers such as N-Acetylaspartic acid, suberic acid and isoallolithocholic acid can be provided. A new path is provided for early intervention of the disease state to improve the pregnancy outcome, and a new drug target is provided for evaluation of the endometrial function of the polycystic ovarian syndrome.

This invention discloses a method, prediction method, and prediction device for constructing a preeclampsia prediction model based on temporal multimodal data, relating to the field of preeclampsia risk prediction technology. The construction method includes: acquiring multimodal temporal feature data of pregnant women with known pregnancy outcomes to construct a time-series dataset; the pregnant women with known pregnancy outcomes include those with and without preeclampsia; training a graph attention network and a fully connected network using the time-series dataset; embedding the resulting missing value fitting model as an embedding layer into a gated recurrent unit; and obtaining the preeclampsia prediction model after training with the time-series dataset. In this invention, the prediction model processes missing data through a missing value fitting model, effectively recovering missing information and ensuring the model can more accurately handle incomplete medical data. Simultaneously, the combination of a gated recurrent unit for capturing and predicting temporal features effectively improves the prediction accuracy of preeclampsia.

The invention relates to an application of a dasatinib and quercetin pharmaceutical composition in preparation of a medicine for improving the outcome of elderly adverse pregnancy, belongs to the technical field of biological medicines, and particularly discloses an application of the dasatinib and quercetin pharmaceutical composition. The technical problem of placenta dysfunction caused by elderly pregnancy is solved. The dasatinib and the quercetin form the pharmaceutical composition, so that the autophagy activity of trophoblasts is promoted, DNA (deoxyribonucleic acid) damaged cells are eliminated, the adverse pregnancy outcome caused by the elderly is remarkably improved, the embryo absorption rate is reduced by about 10%, and the weight of a fetus is increased by about 20mg. The invention provides a new targeted intervention strategy for the outcome of elderly adverse pregnancy.

The present application relates to the technical field of medical data fusion processing, and discloses a method and system for predicting adverse pregnancy outcomes of preeclampsia by fusing placental microenvironment image features and serum biomarkers, wherein the method comprises: obtaining digital whole field image of placental tissue section and serum biomarker detection data at the same period; constructing a multi-modal sample data set; extracting multi-scale structure features of placental microenvironment; constructing serum biomarker discriminant features; dynamically fusing placental image features and serum marker features; constructing a prediction model for adverse pregnancy outcomes of preeclampsia and outputting a prediction probability. Compared with the prior art which only relies on single image information or single serum biomarker for risk assessment, it is difficult to realize stable prediction of the coordinated changes of placental microenvironment abnormalities and biochemical abnormalities. Due to the multi-scale image structure analysis, the model generalization ability for predicting adverse pregnancy outcomes of preeclampsia is improved.

The invention discloses application of a PLAC8 promoter methylation promoter in preparation of a product for promoting angiogenesis of a pig placenta, and belongs to the technical field of biological medicines. Experiments prove that PLAC8 as an anti-angiogenesis factor can directly inhibit the angiogenesis function, and DNMT3A can promote placenta vascular development and improve sow farrowing performance by regulating the methylation level of a PLAC8 promoter. In addition, it is determined that daily ration supplementation of methyl donors in the pig placenta vascular development peak period is an important nutrition way for improving DNA methylation of the PLAC8 promoter region. According to the method, the placenta injury mechanism under the adverse pregnancy outcome is directly determined through combination of in-vivo and in-vitro experiments, a theoretical basis is provided for analysis of a regulation strategy for promoting pig placenta angiogenesis and improving sow reproductive performance from epigenetics, and the accuracy and credibility of a result are improved.

The present invention belongs to the field of medical technology and specifically relates to the use of a mulberry leaf aqueous extract in improving adverse pregnancy outcomes caused by PM2.5. The mulberry leaf aqueous extract can effectively improve adverse pregnancy outcomes caused by PM2.5; the mulberry leaf aqueous extract prevents and treats adverse pregnancy outcomes caused by PM2.5 by reducing the biological damage to trophoblast cells caused by PM2.5.

The invention discloses a blood mtDNACN-based system, method and application for evaluating an adverse pregnancy outcome risk, and the system comprises a data obtaining module which is used for obtaining blood mtDNACN detection data; the risk assessment module is used for storing a pre-constructed causal risk assessment model; and the result output module is used for outputting a risk assessment result. The model is constructed based on a Mendel randomization method, SNP significantly related to blood mtDNACN is used as a tool variable, and the lactic acid metabolism level hybrid effect is innovatively corrected, so that the lactic acid metabolism level hybrid effect of a subject is corrected without depending on lactic acid parameters of the subject. The causal association between the blood mtDNACN and the specific adverse pregnancy outcome (including gestational hypertension, preeclampsia, premature rupture of fetal membranes and the like) is accurately determined. According to the scheme provided by the invention, more reliable and anti-hybrid individualized risk assessment can be realized, and a new tool is provided for health management in the gestation period.

The invention belongs to the technical field of prenatal detection, and discloses application of a fetal side ventricle broadening karyotype-CNV-seq-WES stepped detection strategy in prenatal genetic counseling and clinical prognosis analysis, retrospective queue research design is adopted, 166 cases of FVM diagnosed by prenatal ultrasound are incorporated, and the detection strategy is applied to prenatal genetic counseling and clinical prognosis analysis. The system analyzes the relevance of FVM severity, anatomy types and chromosome abnormalities. The clinical application value of the genetic detection technology is evaluated by comparing genetic detection results and pregnancy outcomes of different subgroups. Through the analysis, more information is provided for the fetal medicine multidisciplinary team, so that the quasi parents are helped to obtain more comprehensive prenatal consultation and decision support.

This invention provides a method and system for integrated data correlation analysis based on clinical features and molecular indicators, belonging to the field of medical data processing and intelligent prediction technology. The method includes: preprocessing collected clinical feature data and molecular indicator data to obtain a standardized structured dataset; extracting key clinical feature subsets and key molecular indicator subsets from the standardized structured dataset, and fusing them to generate a unified multidimensional fusion feature vector; dynamically calibrating at least three clinical phenotypic benchmarks in the unified multidimensional fusion feature vector using a clinical feature data spectrum, whereby the clinical phenotypic benchmarks are defined based on age feature spectrum nodes, infertility course trajectory critical scaling, and endometrial thickness quantification cutoff values. This invention can effectively complete the integrated correlation analysis of clinical features and molecular indicators and predict pregnancy outcomes, meeting the needs of precision clinical diagnosis and treatment.

The present invention discloses an estradiol biosensor and its construction method and application, belonging to the field of biosensor technology. The estradiol biosensor of the present invention comprises a sensing substrate and a DNA molecular machine; the sensing substrate is a gold electrode modified with an IP-BP double chain; the DNA molecular machine comprises an Aptamer-TP double chain and an FP-N3 probe. The biosensor of the present invention uses an estradiol aptamer probe to specifically identify estradiol, constructs a DNA molecular machine for signal cyclic amplification, and uses an atom transfer radical polymerization (ATRP) reaction to perform polymerization growth of electrical signals, thereby achieving efficient and amplified detection of estradiol, improving detection accuracy and sensitivity, and can be applied to the accurate detection of E2 content in clinical blood samples. It has important application value in research fields such as predicting pregnancy outcomes, endocrine diseases, and precocious puberty.

The invention discloses application of CD52 protein in preparation of a medicine for treating recurrent abortion, and belongs to the technical field of biological medicine. It is found that the CD52 protein can inhibit abnormal activation of maternal-fetal interfacial effect T cells in a targeted mode and reduce release of proinflammatory factors (such as IFN-gamma), so that immune tolerance imbalance is reversed, and the pregnancy outcome is improved. The CD52 protein is applied to treatment of the recurrent abortion for the first time, and the CD52 protein has the advantages of being high in targeting performance and high in safety.

The invention relates to an embryonic development potential deep learning prediction method based on blastocyst transcription sequencing, which can overcome the difficulty of DNA / RNA co-sequencing for blastocyst trophoderm trace cells, and additionally obtain transcriptome RNA-seq data on the basis of not influencing the existing PGT-A technology to obtain chromosome CNV through DNA sequencing. Differential expression genes (DEGs) are found, and the developmental potential of an embryo is predicted by analyzing the expression profiles of the genes. A blastocyst pregnancy outcome prediction model is established and serves as a method for screening embryonic development potential clinically, pregnancy development potential prediction is rapidly carried out, pregnancy time can be shortened, multiple pregnancy failures are reduced, clinical efficiency is improved, and important contribution is made to the field of reproductive medicine.

The invention discloses a marker for predicting the risk of premature delivery, and the marker is an amniotic fluid metabolite which is selected from one or more of Corydaline, Diethanolamine and Loureirinb. The prediction method comprises the following steps: analyzing the expression quantity of metabolites in a maternal amniotic fluid sample, and predicting whether a subject has the risk of premature delivery or not according to the expression quantity. The kit is used for detecting the expression quantity of metabolite with high marking effect in an amniotic fluid sample of a pregnant woman, is high in sensitivity and specificity, is used as an auxiliary means for predicting the premature delivery risk of the pregnant woman, is used as a diagnosis means for the pregnant woman with the premature delivery risk or premature delivery, improves the pregnancy outcome of the pregnant woman, improves the pregnancy quality of the pregnant woman, and reduces the labor intensity of the pregnant woman. The occurrence of neonatal adverse events is reduced; according to the invention, the variety of biomarkers for predicting the premature delivery risk is expanded.

A probiotic composition is provided comprising a new Lactobacillus gasseri strain deposited under the Budapest Treaty in the Spanish Type Culture Collection (CECT) under accession number CECT 30648, or a bacterial strain derived thereof. Also provided are uses and methods thereof for the treatment of urogenital infections, in particular for bacterial vaginosis, aerobic vaginitis, urinary tract infections, vulvovaginal candidiasis, vaginal dysbiosis and unfavorable pregnancy outcomes. The probiotic composition is also useful for the treatment of other urogenital diseases or conditions, particularly, hyperoxaluria and oxalate-related health conditions.

The invention relates to a machine learning and biomedical technology, in particular to a pre-eclampsia prediction system based on retina parameters, which comprises a data acquisition module used for acquiring clinical information data and fundus photo data; the fundus parameter extraction module is used for carrying out retina capillary segmentation on the fundus photo data and then carrying out quantification to obtain fundus parameters; the data set preparation module is used for matching and processing the fundus parameters and the clinical information data according to the identity of the pregnant woman to generate a data set for constructing and developing a prediction model; the prediction model construction and development module is used for constructing and training a prediction model by integrating clinical risk factors, MAP and fundus parameters based on a logistic regression (LR) algorithm according to the data set; and the prediction module is used for carrying out real-time acquisition and online risk prediction on the clinical information data of the pregnant woman and the fundus photo data. By noninvasively integrating the fundus photo, the MAP and the pregnant woman characteristic data, the early efficient prediction of the PE and the newborn bad pregnancy outcome is realized.

The utility model provides an amniotic fluid puncture needle, and belongs to the technical field of medical instruments. The amniotic fluid puncture needle comprises a puncture assembly and a storage assembly, the puncture assembly comprises a needle head, a connecting tube, a three-way valve, a first shunt tube and a second shunt tube, the connecting tube is connected to the needle head, the storage assembly comprises connectors and a vacuum tube, the first shunt tube and the second shunt tube are both communicated with the connectors, and the vacuum tube is communicated with the first shunt tube and the second shunt tube. By arranging the needle head, the connecting pipe, the three-way valve, the first flow dividing pipe, the second flow dividing pipe, the connector and the vacuum pipe, amniotic fluid in the connecting pipe is divided and guided through the three-way valve, negative pressure suction is conducted in cooperation with the connector and the vacuum pipe, and therefore the first flow dividing pipe and the second flow dividing pipe can be conveniently and alternately used; the extraction continuity is guaranteed, the effect is improved, meanwhile, the manual extraction labor intensity of personnel is relieved, and the risk of the bad pregnancy outcome of the pregnant woman is reduced.

This invention discloses a method and system for predicting pregnancy outcomes in ovulation induction cycles for PCOS patients, belonging to the field of medical artificial intelligence technology. The method includes: acquiring static and dynamic features of PCOS patients; extracting three time-series derived features from the dynamic features: dominant follicle growth rate, multiple follicle synchronous development index, and follicle size uniformity; inputting the static features into a static channel composed of a fully connected neural network, and inputting the time-series derived features into a dynamic channel composed of a gated recurrent unit network; concatenating the outputs of the two channels in a fusion layer and outputting the pregnancy probability through a classification head. This invention, through a dual-channel architecture that fuses baseline clinical parameters and follicle growth dynamic features, achieves a prediction AUC of 0.79, providing effective support for ovulation induction treatment decisions for PCOS patients.

The invention relates to the field of pharmaceutical preparations, and particularly discloses a medicament for treating diabetes mellitus at the early stage of pregnancy and a preparation method thereof. The invention discloses a medicament for treating diabetes mellitus in early pregnancy. The medicament is prepared from the following raw materials in parts by weight: 1 to 2 parts of metformin, 0.5 to 1 part of vitamin D, 0.4 to 0.8 part of insulin aspart, 0.3 to 0.4 part of Chinese yam polysaccharide, 0.2 to 0.4 part of mulberry twig extract and 0.1 to 0.2 part of resveratrol. The preparation method comprises the following steps: mixing the metformin, the vitamin D, the insulin aspart, the Chinese yam polysaccharide, the mulberry twig extract and the resveratrol, grinding, and pressing into tablets. The medicament disclosed by the invention is used for preventing and treating early-stage diabetes mellitus in pregnancy, is beneficial to intervention of the early-stage diabetes mellitus, and reduces adverse pregnancy outcomes.

This invention relates to the field of medical data analysis, and more particularly to a method for assessing the risk of pregnancy outcomes in pregnant women based on multifactor feature analysis. The method includes: acquiring individual measured time-series datasets and baseline reference data for physiological expectations; obtaining a gestational age-specific pathological surge penalty factor by weighting the ratio of angiogenic factors to anti-angiogenic factors; obtaining a cross-system pathological cascade time coupling factor by temporally tracing and coupling abnormal deviations in vascular system indicators and blood system indicators; obtaining a fused feature vector by correcting and fusing the initial linear regression slope features; and obtaining the pregnancy outcome risk assessment result by performing machine learning prediction on the fused feature vector. This method solves the problem that existing prediction methods based on linear regression slope extraction and feature splicing cannot effectively identify gestational age-specific early high-risk signals and cross-system short-term pathological cascade signals.

The invention relates to a microfluidic device, method, and use for the continuous, label-free isolation of motile, morphologically normal spermatozoa from semen samples This invention offers a gentle, reliable, and efficient platform for sperm selection, serving as an alternative to centrifugation-based techniques in ART laboratories. By maintaining the structural and genetic integrity of sperm, it improves fertilization success, embryo quality, and pregnancy outcomes. The platform also reduces variability between technicians and limits exposure to reactive oxygen species (ROS), ensuring consistent clinical performance. Beyond its application in fertility treatments, the system can be used as a diagnostic tool to assess sperm motility disorders, susceptibility to oxidative stress, and DNA fragmentation dynamics under different environmental conditions or drug exposures.

The invention discloses a deep endometriosis postoperative pregnancy outcome prediction and model construction method and device, and belongs to the field of gynaecology and obstetrics data processing, and the method comprises the steps: collecting and dividing retrospective collection data of a first target group before a first time point, and obtaining a first training set and a first verification set; after a plurality of different types of preset prediction models are trained through the first training set, screening a first prediction model from the trained preset prediction models through the first verification set; after the first time point, collecting and dividing prospective collection data of a second target population, and obtaining a second training set and a second verification set; when it is judged that the first prediction model needs to be calibrated according to the second verification set, the first prediction model is finely adjusted according to the second training set; and taking the finally obtained first prediction model as a deep endometriosis postoperative pregnancy outcome model. According to the method, the postoperative pregnancy probability of the deep endometriosis patient can be predicted through various clinical risk factors.

The present application relates to the technical field of biotechnology, and particularly relates to application of chicoric acid (especially LCA) in preparation of a medicine for preventing, alleviating and / or treating adverse pregnancy outcomes caused by over-activation of IFN-I.

Diagnostic microarray devices, kits, and methods of treating or reducing the occurrence of various conditions or diseases are disclosed, wherein the conditions or diseases include (but are not limited to) periodontal disease, Alzheimer's disease, cardiovascular disease, arthritis, and adverse pregnancy outcomes. The devices, kits, and methods utilize an analysis of single nucleotide polymorphisms (SNPs) from various interleukins.

The invention belongs to the technical field of animal breeding. More specifically, the invention relates to a method for predicting ewe embryo transplantation pregnancy results. The research finds that luteinizing hormone, cortisol and prostaglandin E2 in the estrus period of the ewe have significant correlation with the pregnancy result after the ewe embryo transplantation in a specific concentration range for the first time, and ROC curve analysis proves that the three can be used as biomarkers for predicting the pregnancy result after the ewe embryo transplantation. On the basis, the invention provides a method for predicting the pregnancy result of ewe embryo transplantation, and the pregnancy result is predicted according to the concentration of the reproductive hormone by detecting the concentration of the reproductive hormone in the peripheral blood of the receptor ewe in the estrus period. According to the method, pregnancy potential evaluation can be realized before transplantation, and the prediction timeliness is remarkably improved. In addition, breeding managers can screen high-pregnancy-potential individuals accordingly, and breeding efficiency is improved. The hormone abuse condition in embryo transplantation is reduced, the culture cost is reduced, and the method has good application prospects and value.

Disclosed is an approach that may include generating and / or using a predictive machine learning classifier comprising one or more artificial neural networks. The classifier is configured to output a prediction related to developing preeclampsia (e.g., early onset preterm preeclampsia) during a current pregnancy of a patient based on health characteristics and one or more DNA metrics. The health characteristics and DNA metrics, such as total cell-free DNA (cfDNA) and fetal fraction (FF), may be obtained during a routine and non-invasive or minimally-invasive prenatal screening. The predictive machine learning classifier may be generated by applying deep learning techniques to data on subjects in a cohort. The data may comprise features corresponding to outcomes of prior pregnancies, health indicators, and one or more cfDNA measurements. First trimester risk assessment for preterm preeclampsia can identify patients most likely to benefit from preventative treatment protocols with a minimal or low level of intervention.

The present application relates to the field of microbial technology, and specifically discloses Lactobacillus murinus Mafic1501 and its application in improving placental function of intrauterine growth restriction maternal and / or embryo development of intrauterine growth restriction. L. murinus The present application finds that adding Lactobacillus murinus Mafic1501 to the mother can improve the placental function of the mother and the development of the fetus, and further provides a strain of Lactobacillus murinus (Mafic1501) and its application. The Lactobacillus murinus Mafic1501 is preserved in the China General Microbiological Culture Collection Center, and the preservation number is CGMCC NO.32163. It provides an effective nutritional control scheme for alleviating the adverse pregnancy outcomes of intrauterine growth restriction.

This invention relates to the field of biotechnology and provides a gene-modified mouse model for tracking migratory organisms, its construction method, and its applications. The invention achieves precise labeling of endogenous migratory organisms by fusing the key structural protein TSPAN4 of the migratory organism with the fluorescent tag RFP and the modification tag Avi-tag, and site-specifically integrating it into the H11 site of mice, thus obtaining a TSPAN4-overexpressing transgenic mouse model. By introducing an LSL structure, the fusion gene is kept in a state of expression shutdown, achieving temporal and spatial specific activation only after mating with tissue-specific Cre tool mice. Multidimensional validation has shown that this model can accurately track migratory organisms in placental trophoblast cells, providing a standardized tool for assessing disease progression under physiological and pathological conditions through differences in migratory organism trajectory, inclusion packaging, and assembly, and can be directly applied to mechanistic studies and drug screening for diseases such as adverse pregnancy outcomes.

This invention proposes a pregnancy outcome prediction system based on electronic medical records. The system includes a data acquisition terminal, a data transmission device, a cloud terminal, and a data prediction terminal. The data acquisition terminal is used to collect electronic medical record information of pregnant users from a database in real time and dynamically adjust the information update query frequency based on database data retrieval parameters. The data transmission device is used to establish data communication connections and adjust communication frequencies between the data acquisition terminal and the data prediction terminal, between the data acquisition terminal and the cloud terminal, and between the data prediction terminal and the cloud terminal. The data prediction terminal is used to obtain pregnancy prediction results based on preprocessed medical record data and to visualize the prediction results. The cloud terminal is used to store the data information sent by the data acquisition terminal and the data prediction terminal in the cloud.

The application discloses application of cinnamyl aldehyde in preparation of a medicine for improving iron deficiency anemia and adverse pregnancy outcomes of pregnant women during pregnancy, and after treatment with the cinnamyl aldehyde, anemia symptoms of the pregnant women caused by iron deficiency during pregnancy can be significantly relieved, and adverse pregnancy outcomes caused by iron deficiency anemia can also be relieved, and the specific performance is relieving fetal growth restriction, thereby providing a new medicine and treatment selection for treating iron deficiency anemia and improving adverse pregnancy outcomes of the pregnant women during pregnancy.