1544 results about "Obstetrics" patented technology

The invention relates to an ovarian reserve hypofunction prediction method based on multi-data fusion, and the technical scheme comprises the following steps: regularly collecting biomarker data related to ovarian reserve, including anti-mullerian canal hormone AMH, follicle stimulating hormone FSH, luteinizing hormone LH, estradiol E2, and ultrasonic image data including follicle quantity and ovarian volume; acquiring dynamic change curve data and capturing the change trend of the ovarian reserve function when the acquisition time point covers the key stage of the menstrual cycle; analyzing the biomarker data acquired for multiple times by using an LSTM deep learning model, and modeling a change trend of the ovarian reserve function of each patient along with time; by analyzing the periodic fluctuation of AMH and FSH biomarkers, the decline time node of the ovarian reserve function in the future is predicted; and on the basis of the LSTM deep learning model of S1.1, performing personalized risk assessment in combination with individual characteristics of patients including age, genes, lifestyles and disease histories.

The invention provides an ewe estrus stage identification method and system, and relates to the technical field of precise and intelligent breeding, and the method comprises the steps: based on the ewe estrus stage identification method, obtaining genital tract physiological parameters and multi-dimensional motion data of ewes in a target breeding region, processing the genital tract physiological parameters and multi-dimensional motion data, constructing an estrus stage feature matrix, and carrying out estrus stage identification on the ewes in the target breeding region; and constructing a preset ewe estrus stage identification model based on a bionic element network algorithm, inputting the estrus stage feature matrix into the preset ewe estrus stage identification model, performing training, verification and testing, adjusting weight parameters according to a verification result, performing model evaluation according to a test result, and finally obtaining the ewe estrus stage identification model. And continuously acquiring new genital tract physiological parameters and multi-dimensional motion data in real time, constructing a new estrus stage feature matrix, and inputting the new estrus stage feature matrix into the ewe estrus stage identification model to obtain the estrus stage of the ewes in the target breeding area. The estrus stage of the ewe can be identified timely and accurately.

The invention provides a male product delay spray and a preparation process thereof, and relates to the field of delay sprays. The preparation process of the male product delayed spray comprises the following steps: S1, preparing water and ethanol, and uniformly stirring and mixing; s2, extracting fructus cnidii, herba epimedii, flos caryophylli, pericarpium zanthoxyli, herba cistanche, herba cynomorii and piper nigrum respectively; s3, obtaining a corresponding extract according to the step S2; s4, putting the obtained extract into water and an ethanol dissolving solution; s5, increasing the stirring speed, heating, and fully dissolving and mixing; s6, stopping stirring and cooling to room temperature; and S7, performing filling. According to the invention, the plant extract is adopted as an effective component, and the special pepper kava extract is selected, so that the irritation can be obviously reduced, the delay effect can be obviously improved, and the effects of reducing the skin sensitivity of the penis and improving the sexual intercourse time can be achieved by applying the plant extract to the skin surface of the male penis.

Provided in the present invention are a method for constructing a pre-eclampsia risk assessment prediction model, and a prediction product, a prediction system, and a related application of the method. Specifically, the method of the present invention comprises: constructing a logistic regression analysis model on the basis of acquired clinical indexes of a pregnant woman, and obtaining the prior probability of early-onset pre-eclampsia or late-onset pre-eclampsia in the pregnant woman; performing median-of-multiples calibration on an acquired MAP, IGFBP1 and / or PLGF of the pregnant woman, and respectively constructing a multivariate normal distribution model for a sick pregnant woman and a multivariate normal distribution model for a healthy pregnant woman on the basis of an MAP MoM value and an IGFBP1 MoM value and / or a PLGF MoM value, so as to obtain the conditional probability of early-onset pre-eclampsia or late-onset pre-eclampsia in the pregnant woman; and in view of the prior probability and the conditional probability, calculating the posterior probability of early-onset pre-eclampsia or late-onset pre-eclampsia in the pregnant woman on the basis of a Bayesian model. In the present invention, the detection of related protein markers and the obtaining of maternal clinical information data are relatively easy, the accuracy of predicting early-onset pre-eclampsia and late-onset pre-eclampsia is relatively high, and clinical popularization and application are facilitated; therefore, the present invention is of great value to the prevention and early diagnosis of a disease.

The invention relates to the technical field of biomedicine, in particular to a gestational period premature delivery risk auxiliary prediction method and system, and the method comprises the steps: obtaining the historical body data and delivery cycle of a pregnant woman, and determining the historical premature delivery degree of the pregnant woman according to the delivery cycle; according to the premature delivery degree difference between different historical pregnant women and the deviation degree change condition difference of the same type of body data during each physical examination, determining the premature delivery correlation degree of different types of body data of the historical pregnant women; clustering the historical pregnant women according to the deviation time difference of the same type of body data among different historical pregnant women, determining the overall correlation of each type of body data according to the number of pregnant women in the cluster and the premature delivery correlation degree of the corresponding type of body data, and screening out the target type of body data; and based on the body data of the target type of the historical pregnant woman during different times of physical examination, constructing a premature delivery prediction model to perform premature delivery prediction. According to the method, the accuracy of premature delivery prediction is effectively improved.

The present invention provides an infant formula milk powder and a preparation method thereof. The infant formula milk powder contains a protein composition capable of improving the digestibility of protein in the infant formula milk powder; wherein, based on the total protein content of the infant formula milk powder as 100%, the protein composition contains 13.0%-50.5% of α-lactalbumin and 15.0%-35.0% of β-casein. The technical solution of the present invention can significantly improve the digestibility of whey protein in infant formula milk powder.

The embodiment of the invention provides a method and a system for predicting serious postpartum hemorrhage. The method comprises the following steps of: firstly, acquiring multi-modal medical image data, and preprocessing and aligning the multi-modal medical image data; performing segmentation processing on the image through a sliding window strategy, and extracting structural features, texture features, hemodynamic features and blood vessel distribution features from a segmentation result; then the features serve as nodes to construct a graph structure, the relation between the nodes is coded through a graph convolutional network, and the relevance of the features on the topology level is calculated; and finally, fusing the features according to the relevance, inputting a prediction model, and outputting a prediction result. According to the method, through multi-feature fusion and multi-modal data integration, the prediction capability and the prediction accuracy are improved, the robustness of the model in different data environments is enhanced, the bleeding risk can be recognized in time in the middle and later periods of pregnancy of the pregnant woman, early intervention and treatment suggestions are provided, and the risk of bleeding is reduced. The occurrence rate and fatality of serious postpartum hemorrhage are obviously reduced.

The invention discloses a blood sampling heat preservation device for animal epidemic disease detection, which comprises a storage box, a heat preservation cavity is arranged in the storage box, a plurality of groups of heating rods are arranged in the heat preservation cavity, an annular conveying belt is arranged in the heat preservation cavity, a plurality of groups of bottle placing seats which are arrayed at equal intervals are arranged on the annular conveying belt, and the bottle placing seats are rotatably connected with the annular conveying belt; sampling bottles are placed in the multiple sets of bottle placing bases, taking and placing holes matched with the sampling bottles are formed in the upper portion of the heat preservation cavity, and sealing plates hinged to the inner walls of the taking and placing holes are installed in the taking and placing holes. The device has the beneficial effects that a second gear at the power output end of a motor is matched with a first gear to drive a bottle placement seat to rotate so as to drive a sampling bottle to rotate, so that sampled blood in the sampling bottle is fully mixed with an anticoagulant, and meanwhile, the sampling bottle is in a heat preservation environment in a heat preservation cavity in the whole process of rotation; blood in the sampling bottle is prevented from going bad when being cooled to influence a subsequent detection result.

The invention provides a gestational diabetes mellitus dynamic risk assessment method and a gestational diabetes mellitus dynamic risk assessment system, and relates to the technical field of gestational diabetes mellitus risk assessment. The collaborative fluctuation intensity of the three core characteristics is accurately quantified by using a matrix norm, a two-factor decision engine is generated by combining postprandial blood sugar daily mean value change direction marks, a long-term metabolism trend under a gestational week differentiation weight is quantified by using a risk coefficient, and a linkage factor is fused with multi-characteristic collaborative fluctuation and a blood sugar short-term change direction. A blood glucose threshold self-adaptive adjustment algorithm is driven in real time, and a traditional static threshold system is thoroughly broken through; an acute event hard interception network is synchronously established, risk assessment result forced coverage and minute-level monitoring activation are triggered through a linkage factor threshold value, and a mechanical response barrier for acute metabolism decompensation is formed; and finally, dynamic risk assessment of the gestational diabetes mellitus is realized.

The invention relates to gestational weight gain prediction. The disclosed concepts are directed to providing protocols, solutions, concepts, designs, methods and systems related to improved prediction of gestational weight gain (GWG). Specifically, during the early stage of pregnancy (e.g., during the first 30 days of pregnancy, or during the first three months of pregnancy), a data sequence describing the weight of a pregnant subject at least twice a day (e.g., after waking up and before falling asleep) is used to determine the historical GWG curve of the subject. Since the energy balance in pregnancy is defined as energy intake equal to energy expenditure plus dynamic energy storage, a particular GWG prediction model is used to generate historical GWG curves, rather than a universal weight gain model. From the historical GWG curve, a future GWG value of the subject may be predicted. The future GWG value may be used to assess pregnancy risk scores, and / or to generate lifestyle recommendations for the subject.

The invention relates to the field of disease animal model construction, and particularly discloses a postmenopausal osteoporosis and knee osteoarthritis co-disease animal model construction method which comprises the following steps: selecting a female animal as an experimental subject; the selected female animals are injected with a GnRH agonist, meanwhile, low-calcium feed feeding and oxidative stress stimulation are conducted, and feeding is conducted for a preset time; detecting bone mineral density and bone trabecula parameters of the fed female animals, and screening qualified female animals meeting set standards; performing meniscus tearing operation on the qualified female animal, and implanting sustained release microspheres loaded with inflammatory factors at the torn part during the operation; carrying out weight-bearing training on the female animal after the operation, and continuing for a set time length; and performing health detection on the female animals at different time points. According to the method, through multi-factor collaborative induction of the PMOP, minimally invasive construction of the KOA and multi-dimensional health detection, accurate simulation of a co-disease pathological process and clinical characteristics is realized, and the authenticity and stability of the model are improved.

The present invention relates to the field of biomedical technology, and more specifically to a method and system for assisting in predicting the risk of premature birth during pregnancy. The method comprises obtaining the physical data and delivery cycles of historical pregnant women, determining the degree of premature birth of the historical pregnant women based on the delivery cycles, and determining the degree of premature birth correlation of different types of physical data of the historical pregnant women based on the differences in the degree of premature birth between different historical pregnant women and the differences in the deviation changes of the same type of physical data during each physical examination. The historical pregnant women are clustered based on the deviation time differences of the same type of physical data between different historical pregnant women, and the overall correlation of each type of physical data is determined based on the number of pregnant women in the cluster and the degree of premature birth correlation of the corresponding type of physical data, thereby screening out the physical data of the target type. A premature birth prediction model is constructed based on the physical data of the target type during different physical examinations of the historical pregnant women to perform premature birth prediction. The present invention effectively improves the accuracy of premature birth prediction.

A kit comprising at least three male condoms, and at least three wearable constriction devices that are physically separate from the condoms. The male condoms are individually packaged in separate compartments, and, the wearable constriction devices are packaged together in a single compartment that is separate from the three male condom compartments. Alternatively, the male condoms are individually packaged in separate compartments, and, the wearable constriction devices are packaged individually in separate compartments that are also separate from the three male condom compartments.

The present disclosure relates to a vaginal system that prevents pregnancy comprised of segesterone acetate and ethinyl estradiol and is configured for thirteen 28-day product-use cycles.

The invention relates to the field of maternal and infant products, and provides a recommended breast pumping method of a breast pump and related equipment, the method comprises the following steps: obtaining a plurality of historical breast pumping data, the breast pumping data at least comprising breast pumping parameter data of a plurality of historical breast pumping periods or breast pumping parameter data in a plurality of preset breast pumping periods; at least one piece of recommended milk sucking data is generated according to the milk sucking parameter data of the multiple historical milk sucking periods or the milk sucking parameter data in the multiple preset milk sucking periods, and each piece of recommended milk sucking data corresponds to one callable milk sucking period or milk sucking parameter in the milk sucking period. According to the method, the recommended breast pumping data are generated through the historical breast pumping data, each piece of recommended breast pumping data corresponds to one callable breast pumping period or the breast pumping parameter in the breast pumping period, so that the breast pump is controlled to work through the breast pumping parameters, and the most suitable breast pumping mode is provided for each mother.

The invention relates to the technical field of puerpera diet management, in particular to a postpartum diet management system and method. The server comprises a data acquisition module, a dimension extraction module, an evaluation module, a diet customization module, a baby data acquisition module and a diet optimization module; wherein the infant data acquisition module is used for monitoring physical state data of an infant born by a puerpera in real time at the first time after the puerpera is postpartum; the judgment module is used for determining the to-be-supplemented nutrient elements missed by the infant and the corresponding missing content according to the body state data corresponding to the infant in each time period; and the diet optimization module is used for optimizing the basic diet scheme according to the basic diet scheme corresponding to each time period of the lying-in woman and the to-be-supplemented nutrient elements and the deficiency content required by the baby born by the lying-in woman in each time period to form a diet optimization scheme.

The invention discloses an in-vitro fertilization-based method and system for predicting the cumulative live productivity of multiple complete cycles, and the method comprises the steps: obtaining clinical data, embryo information and pregnancy follow-up visit data of a patient, and screening and preprocessing a sample in combination with a collection and discharge standard; feature variables are extracted before treatment, after treatment and at the early stage of pregnancy, an optimal set is determined, and key factors influencing live birth at all stages are accurately captured; after the nonlinear variables are processed by the RCS, a pre-treatment / post-treatment COX regression model and a Logistic regression model are adaptively constructed, and the prediction precision is improved by fitting data characteristics; and meanwhile, by evaluating the iterative optimization model, the variable weight is visually displayed by using a Nomogram graph after the model is qualified. The method can accurately predict the multi-cycle cumulative live productivity, assists a doctor in formulating a personalized scheme, helps a patient to reasonably plan treatment, reduces the time and economic burden of blind treatment, and has clinical practical value and benefits of the patient.

The utility model relates to the technical field of cervix uteri sampling, discloses a side-push type cervix uteri sampler with sampling head storage and anti-pollution functions, and solves the problem that the existing cervix uteri sampler needs medical personnel to cut off a sampling swab and is easy to touch a sampling area to pollute a sample. Through buttons, a connecting rod, a blade and a spring II, in order to avoid direct contact with a disposable sampling rod and pollution of the disposable sampling rod after sampling, the buttons on the two sides of the protective barrel are pressed inwards, and at the moment, the buttons move inwards to push the connecting rod to move inwards to drive the blade to move inwards; the two blades and the cut-off point of the disposable sampling rod are cut off at the same time, the separation work of the disposable sampling rod is completed, a sampling head adhered with a sample falls into a storage bottle, the sampling head can be well stored, the sampling head is prevented from making contact with the sampling head in the direct breaking process, the sampling hygiene is improved, and the sampling efficiency is improved. And the two hands are not contacted with the disposable sampling rod in the sampling process.

The invention discloses an endometrium sampler, which relates to the technical field of medical instruments and is technically characterized by comprising a protective sleeve, a movable tube, a brush rod, a top bead, bristles and a handle, the protective sleeve and the movable pipe are both of a hollow tubular structure, and the movable pipe is arranged in the protective sleeve and can move in the axial direction of the protective sleeve. The brush rod is arranged in the movable pipe, one end of the brush rod is fixedly connected with the handle, and the other end of the brush rod is fixedly connected with the top bead. The section, close to the top bead, of the brush rod is a brush rod front end; the bristles are attached to the front end of the brush rod and incline towards the top bead, and the top bead is of a semi-surrounding cover-shaped structure. During sampling operation, the handle is rotated to drive the front end of the brush rod to rotate, so that the bristles cover an inverted pear-shaped uterine cavity area; after the bristles finish sampling, the movable pipe is controlled to move towards the top bead, so that the bristles are folded and protected by the movable pipe; the sampling efficiency, the sample integrity and the diagnosis accuracy can be improved.

The present invention relates to a blastocyst quality evaluation method and system. The method comprises: inputting a blastocyst multi-focus image into a pre-trained deep learning model to obtain a blastocyst development stage and quantitative scores for ICM and TE; obtaining a blastocyst quality quantitative score by means of the quantitative scores for ICM and TE; and selecting an optimal blastocyst by means of the blastocyst development stage and the blastocyst quality quantitative score. According to the present invention, the quality of blastocysts of the same grade is distinguished, thereby further quantifying the overall quality of an embryo.

The utility model provides an artificial insemination tube assembly, which belongs to the technical field of insemination tubes and comprises a storage tube, a push rod and an annular air bag, the push rod and the annular air bag are arranged on the storage tube, a feeding tube is arranged on the side wall of one end of the storage tube, and a seminiferous duct is mounted at one end of the storage tube. According to the insemination device, the annular air bag arranged on the outer side of the seminiferous duct expands while insemination is conducted, it is guaranteed that the device is fixed, meanwhile, the situation that semen flows back after insemination is effectively prevented, and then the probability of pregnancy is improved, meanwhile, two one-way valves are installed on the two sides of the annular air bag, and after the annular air bag completely abuts against the inner wall of a uterine cavity, the two one-way valves are closed. When the device is taken out, the other one-way valve is forced to be opened and closed to supplement air into the annular air bag from the outside in the subsequent process of taking out the device, so that the push plug is convenient to move to the initial position, and the safety of the device is improved. The subsequent addition and use of the seminal fluid are convenient.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker related to the fertility rate of pigeons at 52 weeks old as well as application and a breeding method of the SNP molecular marker, the molecular marker is located at the 5476830th basic group of the 15th chromosome of a pigeon reference genome colLiv2, C / T polymorphism exists, and based on genotype discovery of the specific SNP molecular marker, the specific SNP molecular marker can be used for identifying the fertility rate of pigeons at 52 weeks old. The fertilization rate of the pigeons with the 52-week age is remarkably higher than that of C / T genotype individuals and T / T genotype individuals, in breeding, the C / T genotype individuals and the T / T genotype individuals are eliminated, and the C / C genotype individuals are reserved, so that early selection of the fertilization rate of the pigeons with the 52-week age can be realized, the breeding accuracy is improved, the breeding progress is accelerated, the breeding cost is saved, and the breeding effect is improved.

Compositions including FSH and hCG for use in the treatment of infertility.

The invention discloses a dairy cow timed insemination method for controlling ovulation time and improving embryo implantation rate, and relates to the technical field of dairy cow breeding. The problems that follicles on ovaries of postpartum cows are not synchronous in development, ovulation time cannot be accurately regulated and controlled, and embryonic development regulation and control after fertilization are lacked are solved. The method mainly comprises the following steps: three times of gonadotropin releasing hormone injection, two times of cloprostenol sodium injection, gonadotropin releasing hormone injection, luteinizing hormone releasing hormone A3 injection, timed artificial semen deposition, and VADE mixed liquid injection. GnRH is used for actively regulating follicular development, 95% or more of the dairy cows are synchronized after 2-3 rounds of starting, then timing insemination is performed, the conception rate of the postpartum dairy cows can be remarkably increased, compared with the prior art, the pretreatment time is short, the synchronous ovulation rate and conception rate of the dairy cows can be increased, the calving interval is shortened, and the survival rate of the dairy cows is increased. The economic benefit of the pasture is obviously increased, and the breeding management level can be improved on the basis.

The present invention relates to improved assisted reproductive technology using highly purified menotropin (HP-hMG) to stimulate follicle development in controlled ovarian stimulation, particularly in women at risk of a high ovarian response to controlled ovarian stimulation.

The invention discloses application of glycyrrhetinic acid in reducing reproductive toxicity of zearalenone to replacement gilts, and belongs to the technical field of animal breeding. Zearalenone can promote advanced development of internal and external reproductive organs such as uterus, ovary, vagina and the like, cause pathological changes of the reproductive organs, disturb the estrus cycle and the like to exert reproductive toxicity on the replacement gilts, so that the reproductive potential of the replacement gilts is influenced. By adding glycyrrhetinic acid into the replacement gilt feed, the development of the uterus, ovary and follicle of the replacement gilt can be promoted, the harm of ZEA to the ovary and uterus of the replacement gilt is reduced, and the estrus initiation of the replacement gilt is improved, so that the breeding potential of the gilt is improved, and the annual productivity of the replacement gilt is improved.

The utility model relates to a breast pump. The breast pump comprises a floating assembly and a detection assembly. When milk is loaded in the milk storage assembly, at least part of the floating assembly floats on the liquid level of the milk in the milk storage assembly; the detection assembly is used for detecting position information of the floating assembly floating on the milk liquid surface. In the milk sucking process of the breast pump, the height of the milk liquid level in the milk storage assembly is increased along with increase of the amount of milk in the milk storage assembly, the height of the floating assembly floating on the milk liquid level changes, then the floating assembly gets close to or away from the detection assembly under guiding of the guiding piece, detection data of the detection assembly is changed, and the detection accuracy of the breast pump is improved. Therefore, the milk level height and the milk amount in the milk storage assembly are calculated according to data detected by the detection assembly.

The present invention relates to a process for determining pregnancy and / or a pregnancy stage of an ungulate from its feces.

The invention relates to the technical field of medical detection, in particular to an endocrine hypertension screening method based on immunological analysis, which comprises the following steps: collecting a random urine sample, removing interferents by using a composite nano adsorbent, and synchronously detecting hormones such as aldosterone, methoxyadrenaline and cortisol and metabolites thereof by using a high-throughput immunity analyzer; integrating detection data based on a dynamic threshold algorithm to generate a screening report, carrying out weighted scoring on positive samples in combination with clinical features, screening high-risk candidate samples, carrying out 24-hour urine retest on the high-risk samples, and if a retest result is still positive, carrying out referral treatment to a specialized department for disease cause definite diagnosis; according to the method, the technical problems of complex sample treatment, low multi-step efficiency and high false positive rate in the prior art are solved, efficient and accurate screening of endocrine hypertension is realized, and reliable support is provided for early diagnosis and targeted treatment.

The invention discloses a structural variation molecular marker located on a pig chromosome 7 and related to the lactation ability of a sow. The structural variation molecular marker is a DNA (deoxyribonucleic acid) fragment which is inserted between the 112024896 bp site and the 112024896 bp site on a chromosome 7 of an international pig reference genome 11.1 version, wherein the nucleotide sequence of the DNA fragment is shown as SEQ ID NO: 1; the genotype of the gene is T / T, T / INS and INS / INS. The structural variation molecular marker provided by the invention obviously influences the total weight gain character and the lactation ability character of the 7-day-old sow, and by breeding the pig with the structural variation molecular marker genotype of T / T, the lactation ability of the sow can be obviously improved, and the survival rate and the weaning weight of piglets are increased.