Application of Artificial Insemination in Selective Breeding of Native Beef Cattle in Wenzhou

[Objective]The paper was to improve the quality and growth rate of native yellow cattle in Wenzhou.[Method]Three groups of cattle were subjected to artificial insemination using frozen semen from Wagyu bull.The groups consisted of 20 native yellow cattle,20 Angus catle,and 20 Luxi yellow cattle.The heifers were subsequently evaluated for body size and body weight,and underwent treatment with estrus synchronization,artificial insemination,and early pregnancy diagnosis.[Result]The mean body size and body weight of native yellow cattle were found to be significantly lower than those of Angus cattle and Luxi yellow cattle(P<0.05).The estrus synchronization rate and mating rate of native yellow cattle were both 100%,while the corresponding rates for Angus cattle and Luxi yellow cattle were 90%and 95%,respectively.The ultrasound examination conducted on the 32m day following the mating revealed a distinct image of gestation sac,which,when considered alongside the findings of the rectal examination,may be indicative of pregnancy.The conception rates were 75%,72%,and 74%for native yllow cattle,Angus cattle,and Luxi yellow cattle,respectively.[Conclusion]The reproductive performance of native beef cattle is relatively superior.

Bacteriospermia among smallholder artificial insemination boars in the Philippines and potential associated factors

Objective:To determine the prevalence of bacteriospermia,the bacterial load,and the potential factors associated with bacterial contamination in boar semen collected by local smallholder artificial insemination operators.Methods:Fifteen individual raw semen samples were collected from locally available artificial insemination boars owned by different smallholder boar operators within the 5th district of Leyte,Philippines and were subjected to standard bacteriological culture and identification,including a survey of potentially associated factors.Prevalence and bacterial count were determined accordingly,while boar characteristics and collection practices were clustered following agglomerative hierarchical clustering technique.Results:One hundred percent contamination with a bacterial count of(2.01±0.38)×10^(3) CFU/mL was observed.At least 73.33%of the samples were positive for Bacillus spp.,while other identified isolates included Enterobacter spp.,Staphylococcus spp.,E.coli,Pseudomonas spp.,Citrobacter spp.,and Klebsiella spp.Conclusions:Despite the high prevalence of bacteriospermia,the bacterial count is low.Nevertheless,on-farm practices on boar health and management,semen collection,and sanitation as well as the enhancement of basic protocols to control contamination should be conscientiously considered in smallholder artificial insemination operation.

Artificial Insemination of Cherry Valley Ducks with Muscovy Ducks

[Objective] To explore artificial insemination technique for production of mule ducks. [Method] Female Cherry Valley ducks were artificially inseminated with semen collected from male Muscovy ducks by massage method and vagina-insemination method to investigate the effects of insemination dose, insemination interval, insemination time and diluents on fertilization rate. [ Result ] The average fertilization rate was only 39.58%, when the female Cherry Valley ducks naturally mated with the male Muscovy ducks. However, it was increased to 74.79% by artificial insemination. The fertilization rate was 75.24% after semen was diluted by PBS buffer, while it was 75.16% after semen was diluted by Lake＇s buffer; however, there was not significant difference between the fertilization rate of the diluted semen and that of fresh semen （74.10%）. After semen was respectively diluted by PBS buffer and Lake＇s buffer and then stored at 5 ℃ for 24 h, the fertilization rate was low, respectively 23.76% and 34133%. [ Conclusion] Artificial insemination technology can reduce insemination dose and increase fertilization rate in production of mule ducks.

Study on Key Technique of Artificial Insemination for Silkworm,Bombyx mori

[Objective] The aim of this study was to investigate the efficient technique of artificial insemination for silkworm. [Method] Sperms were extracted from bursa copulatrix of female moths mated for 30 min through extruding and centrifugal method, and then the semen was injected into other virgin moths with trypsinase. [ Result] A high-effective collection technology of spermatids from silkworm was established successfully, 50 μl semen could be collected by only one person in each hour. The survival rate of spermatids was over 80% in vito after collected from bursa copulatrix, while the obtained semen was quite pure and the average fertilization rate of silkworm was 76,5%. [ Conclusion] The establishment of high-effective semen extraction technique of silkworm provides the technical basis for studies on other related techniques for silkworm sperm.

Efficiency of Artificial Insemination in Giant Pandas at the Wolong Breeding Center

The goal of the giant panda ( Ailuropoda melanoleuca ) breeding program is to develop a self sustaining,genetically diverse population.Due to the common problems about sexual incompatibility and a limited number of captive born males that breed naturally,artificial insemination (AI) has become a critical genetic management tool.It is common practice,however,to combine natural mating and AI using semen from non breeding males.From 1998 to 2000 at the Wolong breeding facility,12 of 18 (66.7%) females produced 20 cubs following combined natural mating and AI.The objective of this study was to determine the efficiency of AI without natural breeding.In 1998 and 2000,seven females were anesthetized for transcervical AI on two consecutive days.Ejaculates from six males were collected by electroejaculation,diluted in an egg yolk diluent containing 0% or 4% glycerol and used either fresh or following cold storage at 4℃ (for 24 or 48 h) or cryopreservation using the pellet freezing method.Mean (±SEM) ejaculate traits in six male sperm donors were:ejaculate volume,3.3±0.5 ml;sperm concentration,1,429.8±235.4×10 6/ml;sperm motility,81.7±2.1%;progression (0～5,5=best),3.1±0.1;and normal sperm,79.3±9.2%.For AI (n = 14) in seven females,mean inseminate traits were:spermic volume inseminated,2.4±0.3 ml;sperm motility,73.5±2.9%;progression,2.5±0.1;and total motile sperm inseminated/AI,684.2±118.2×10 6.Four of seven (57.1%) females became pregnant and produced five cubs of which four survived.Mean gestation and litter size was 131.5±9.7 days and 1.3±0.3 cubs/litter,respectively.These results indicate that the efficiency of AI is sufficient for recovering valuable genes from non breeding individuals to enhance genetic diversity in the ex situ population of giant pandas.

Lazzaro Spallanzani: pioneer of artificial insemination, multidisciplinary research, and scientific dissemination

Lazzaro Spallanzani(1729-1799)was a father of modern biology,with peculiar traits such as a multidisciplinary approach and penchant for scientific dissemination.Spallanzani consistently contributed to modern reproductive medicine by implementing experimental methods for the first historically successful artificial insemination.Nevertheless,he participated in discoveries pertaining to blood circulation,digestion,and respiration.Widely known in Europe in the eighteenth century,his fame prolonged to the following century,not exclusively through scientific acknowledgments,but even in literature.Nowadays,the figure of Spallanzani experience a kind of neglect and it would appear essential to maintain his work in the light of the history of medicine.

Estrus Synchronization and Artificial Insemination with Fresh and Chilled Semen in Assaf Ewes

This paper aims to study the efficiency of two short-term progestagen (FGA vs. MAP) + eCG treatments in estrus synchronization and artificial insemination (AI) with fresh or chilled semen in Assaf ewes fertility rate. All ewes received a subcutaneous implant of exogenous melatonin 45 days before been treated with short-term progestagens + eCG. By June 1st, ewes were divided in two groups: half was treated with an intravaginal sponge impregnated with 20 mg of FGA and the other half with an intravaginal sponge impregnated with 60 mg of MAP. Progestagen treatments lasted for 6 days. At sponge withdraw, all ewes were injected with 750 IU of eCG. Ovarian activity was assessed by plasmatic progesterone levels before and after progestagens + eCG treatment. Semen was collected by electro ejaculation and extended with Andromed? or OviXcell?. AI was performed 55 hours after eCG administration with fresh or chilled semen. During AI several factors were assessed: vagina mucosa color and lubrication, external cervical Os type, cervical mucous viscosity, semen deposition place and seminal cervix outflow. Semen was deposited as deep as possible without distress or trauma cervix mucosa. All Assaf ewes presented cyclic activity before progestagen + eCG treatments (2nd fortnight of May). Short-term progestagen + eCG treatments were equally efficient (100.0%). About 76.5% of Assaf ewes were pregnant 41 days after AI. Fertility rate was influenced by external Os type, semen deposition place and seminal cervix outflow. However, this rate was not conditioned by vaginal color or lubrication, cervical mucus viscosity, semen preservation technic and semen extender.

Factors Influencing the Superovulation and Artificial Insemination of Sheep

[Objective] This study aimed to find out a method for low-cost and highly efficient sheep superovulation treatment and artificial insemination. [Method] The factors those probably influencing the results of conventional superovulation and insemination, such as combination of FSH hormone and sponge suppository, estrus interval, number of insemination, and ram individuals were analyzed. [Result] The combination of sponge suppository and FSH produced in Beijing exhibited the poorest effect to superovulation, significantly worse than that of other combinations （P0.01）. The FSH produced in Ningbo, combined with sponge suppository or CIDR produced better effect to superovulation. The superovulation effect was better when the interval from the last FSH injection to estrus was 12 h, significantly better than that when the interval was 36 h （P0.01）; and there was no difference in the superovulation results when the interval was 0, 12 and 24 h. The pregnancy rate of two artificial inseminations was significantly higher than that of only one insemination （P0.01）. Rams themselves had significant influence on fertilization results. [Conclusion] The combination of domestic FSH and domestic sponge suppository cost much less and dose not reduce the superovulation results. Better fertilization result can be obtained if the ewes are inseminated twice with the sperm those gave high pregnancy rate.

A new device for deep cervical artificial insemination in gilts reduces the number of sperm per dose without impairing final reproductive performance

Background: The aim of this study was to evaluate the reproductive performance of a new artificial insemination(AI) device specifically designed for gilts(Deep cervical AI, Dp-CAI) by means of which the sperm is deposited deeply in the cervix(8 cm more cranial than in traditional cervical insemination-CAI). New AI techniques have arisen in recent decades in the porcine industry, such as post-cervical artificial insemination(PCAI), which involves depositing the sperm in the body of the uterus [through a catheter(outer tube)-cannula(inner tube)] rather than by CAI. Although the PCAI method has been successfully applied in farm conditions to reduce sperm doses without impairing the reproductive performance, this technique has limitations in gilts mainly because of the difficulty involved in introducing the inner cannula through the cranial part of the cervix. For this reason, the Dp-CAI method described herein may be considered as an alternative to CAI and PCAI methods in gilts.Results: Gilts were divided in two experimental groups: 1) Dp-CAI: gilts(n = 1166) inseminated using 1.5 × 109 sperm/45 m L;2) CAI(as a control group): gilts(n = 130) inseminated using 2.5 × 10~9 sperm/85 mL. The Dp-CAI method was successfully applied in 88.90% of the gilts, with no differences detected between gilts with 1 or 2 previous oestrus cycles, although the catheter could be introduced more deeply in 2 oestrus gilts(P < 0.05). As the length of the insemination device that could not be introduced increased(at the moment of insemination), so the success rate of the Dp-CAI device fell, as did the total number of piglets born. When the reproductive output in CAI and Dp-CAI was compared, none of the parameters analysed [pregnancy and farrowing rates(%), and number of piglets born(total and live)] showed significant differences.Conclusions: The use of the Dp-CAI technique provides a new AI method as an alternative to CAI and PCAI for pigs. The device, especially designed for gilts, was used with a high degree of success reducing conventional sperm doses without impairing reproductive parameters.

Assessment of Artificial Insemination in Camel

The objective of this review is to confer semen collection and processing, and semen deposition technique in camel. Artificial insemination is an important technique to ensure rapid genetic improvement in camels. The use of AI has been reported in camel, although insemination trials are rare. The widely accepted methods of semen collection include electro ejaculation and artificial vagina (AV), but flushing of the epididymis with saline solution can also be used as an alternative. Depending on the method of semen processing, semen is usually used in raw condition or after extension. Whole semen is used within minutes or after few hours in the fresh raw method. In short-term preservation or liquid semen (within a few hours or days) and long-term preservation or frozen semen (months or years), extension of the semen ejaculate is carried out by adding extenders which is required in more efficient use of AI. Semen is extended under different temperatures (30°C, 25°C or 4°C), in short-term preservation. Cryopreservation is used to carry out long-term preservation. Different freezing procedures are represented by packaging methods such as ampoules or in plastic straws with different volumes (0.25, 0.5 or 4 ml) and pellets. The best time for insemination can only be determined by rectal palpation of the ovaries and/or ultrasonography. The other alternative is to inseminate at known intervals following induction of ovulation by hormonal treatment with human-chorionic gonadotropin (hCG) or gonadotropin-releasing hormone (Gn-RH). The semen should be deposited into the uterus at least 24 hours after the onset of ovulation. Pregnancy rates depend on the semen extender, site of deposition and number of sperm deposited. Blood or milk progesterone assays, rectal palpation, and ultrasonic image detection of pregnancy are commonly used approaches of pregnancy diagnosis in camel.

Artificial Insemination Service Efficiency and Constraints of Artificial Insemination Service in Selected Districts of Harari National Regional State, Ethiopia

The study was conducted to evaluate efficiency of artificial insemination (AI) service and constraints of AI service selected Districts of Harar National Region State, Ethiopia. A total of 320 dairy cows were randomly selected from six districts of Harari region;Jin’Eala, Shenkor, Hakim, Dire-Teyara, Aboker, Sofi. Data on dairy cattle management, artificial insemination (AI) service efficiency and constraints of AI service were generated using structured and semi-structured questionnaire. Forty three straws of frozen semen was sampled from the regional AI service centre, thawed and evaluated at the region level for its quality (motility, viability and morphology) following standard procedures. The overall mean percentage of frozen semen motility at regional level was 49.6. Semen production period (batch) and Breed (exotic blood level) had no effect on frozen semen motility. The mean percentage of viable (live) spermatozoa was 58.3. Sperm viability was not significantly influenced by Semen production period (batch) and, breed (exotic blood level). The overall mean percentages of major and minor sperm morphological defects were 5.6 and 21.8, respectively. Frozen sperm major morphological defects were significantly affected (p < 0.05) by Semen production period (batch), however sire breed has no effect (p > 0.05) on frozen sperm major morphological defects. Frozen sperm minor morphological defects were not significantly affected (P > 0.05) by both semen production period (batch) and sire breed (exotic blood level). The mean number of service per conception (NSC) in the current study was found to be 1.6. It was not significantly affected by previous season of calving, previous year of calving and parity. Non-return rate value of Harari region AI service center was 48.1%. Major constraints of AI service delivery system in the study area were feed shortage, problem in heat detection, service charge for AI, distance from AI service centre and husbandry problem. Additional shortage of input for AI service activity particularly semen and liquid nitrogen was reported as constraint of artificial insemination service in the study area, which interrupt smooth delivery of AI service.

Comparative Study of Two Methods of Induction of Estrus and Fertility Following Artificial Insemination in Azawak Zebu in Niger

A comparative of two induction methods of estrus induction and fertility has been carried out on 28 females Azawak zebu in Niger. This study mains chiefly and identifying the most effective method for better inseminations. The females have been divided into two sets following two intra-vaginal devices used. Two sub-sets of 7 females have been formed according to the PMSG dose associated with the treatment. Two inseminations have been carried out. The results are as follows： response to the induction： PRIDe, 57.14%; CIDR-B, 61.53%. Fertility rate： PRIDe, 28.57%; CIDR-B, 38.46%. There has been no significant difference to the estrus induction and fertility, between the PRIDe and the CIDR-B synchronization. Since the two methods virtually lead to the same response rate, the stock breeder can choose one of the methods depending on the cost and by paying attention to the feeding and less stressful factors.

Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.

Explainable Artificial Intelligence(XAI)Model for Cancer Image Classification

The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare environments.It is to make sure that decisions are based on trustworthy algorithms and that healthcare workers understand the decisions made by these algorithms.These models can potentially enhance interpretability and explainability in decision-making processes that rely on artificial intelligence.Nevertheless,the intricate nature of the healthcare field necessitates the utilization of sophisticated models to classify cancer images.This research presents an advanced investigation of XAI models to classify cancer images.It describes the different levels of explainability and interpretability associated with XAI models and the challenges faced in deploying them in healthcare applications.In addition,this study proposes a novel framework for cancer image classification that incorporates XAI models with deep learning and advanced medical imaging techniques.The proposed model integrates several techniques,including end-to-end explainable evaluation,rule-based explanation,and useradaptive explanation.The proposed XAI reaches 97.72%accuracy,90.72%precision,93.72%recall,96.72%F1-score,9.55%FDR,9.66%FOR,and 91.18%DOR.It will discuss the potential applications of the proposed XAI models in the smart healthcare environment.It will help ensure trust and accountability in AI-based decisions,which is essential for achieving a safe and reliable smart healthcare environment.

Artificial Intelligence Prediction of One-Part Geopolymer Compressive Strength for Sustainable Concrete

Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological concrete.In terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part geopolymer.However,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely reported.Therefore,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part geopolymer.The database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing temperature.The performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed GEP.Sensitivity and parametric analysis were also performed to identify the significant contributor to strength.According to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 days.The water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.

Advancements in Barrett's esophagus detection:The role of artificial intelligence and its implications

Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utilized endoscopic images to train an AI model,challenging the traditional distinction between endoscopic and histological BE.This approach yielded remarkable results,with the AI system achieving an accuracy of 94.37%,sensitivity of 94.29%,and specificity of 94.44%.The study's extensive dataset enhances the AI model's practicality,offering valuable support to endoscopists by minimizing unnecessary biopsies.However,questions about the applicability to different endoscopic systems remain.The study underscores the potential of AI in BE detection while highlighting the need for further research to assess its adaptability to diverse clinical settings.

Artificial intelligence in individualized retinal disease management

Owing to the rapid development of modern computer technologies,artificial intelligence(AI)has emerged as an essential instrument for intelligent analysis across a range of fields.AI has been proven to be highly effective in ophthalmology,where it is frequently used for identifying,diagnosing,and typing retinal diseases.An increasing number of researchers have begun to comprehensively map patients’retinal diseases using AI,which has made individualized clinical prediction and treatment possible.These include prognostic improvement,risk prediction,progression assessment,and interventional therapies for retinal diseases.Researchers have used a range of input data methods to increase the accuracy and dependability of the results,including the use of tabular,textual,or image-based input data.They also combined the analyses of multiple types of input data.To give ophthalmologists access to precise,individualized,and high-quality treatment strategies that will further optimize treatment outcomes,this review summarizes the latest findings in AI research related to the prediction and guidance of clinical diagnosis and treatment of retinal diseases.

A Discussion of Artificial Intelligence in Visual Art Education

Since ChatGPT emerged on November 30, 2022, Artificial Intelligence (AI) has been increasingly discussed as a radical force that will change our world. People have become used to AI in which such ubiquitous technologies as Siri, Google, and Netflix deploy AI algorithms to answer questions, impart information, and provide recommendations. However, many individuals including originators and backers of AI have recently expressed grave concerns. In this paper, the authors will assess what is occurring with AI in Visual Arts Education, outline positives and negatives, and provide recommendations addressed specifically for teachers working in the field regarding emerging AI usage from kindergarten to grade twelve levels as well as in higher education.

Artificial intelligence for characterization of diminutive colorectal polyps:A feasibility study comparing two computer-aided diagnosis systems

BACKGROUND Artificial intelligence(AI)has potential in the optical diagnosis of colorectal polyps.AIM To evaluate the feasibility of the real-time use of the computer-aided diagnosis system(CADx)AI for ColoRectal Polyps(AI4CRP)for the optical diagnosis of diminutive colorectal polyps and to compare the performance with CAD EYE^(TM)(Fujifilm,Tokyo,Japan).CADx influence on the optical diagnosis of an expert endoscopist was also investigated.METHODS AI4CRP was developed in-house and CAD EYE was proprietary software provided by Fujifilm.Both CADxsystems exploit convolutional neural networks.Colorectal polyps were characterized as benign or premalignant and histopathology was used as gold standard.AI4CRP provided an objective assessment of its characterization by presenting a calibrated confidence characterization value(range 0.0-1.0).A predefined cut-off value of 0.6 was set with values<0.6 indicating benign and values≥0.6 indicating premalignant colorectal polyps.Low confidence characterizations were defined as values 40%around the cut-off value of 0.6(<0.36 and>0.76).Self-critical AI4CRP’s diagnostic performances excluded low confidence characterizations.RESULTS AI4CRP use was feasible and performed on 30 patients with 51 colorectal polyps.Self-critical AI4CRP,excluding 14 low confidence characterizations[27.5%(14/51)],had a diagnostic accuracy of 89.2%,sensitivity of 89.7%,and specificity of 87.5%,which was higher compared to AI4CRP.CAD EYE had a 83.7%diagnostic accuracy,74.2%sensitivity,and 100.0%specificity.Diagnostic performances of the endoscopist alone(before AI)increased nonsignificantly after reviewing the CADx characterizations of both AI4CRP and CAD EYE(AI-assisted endoscopist).Diagnostic performances of the AI-assisted endoscopist were higher compared to both CADx-systems,except for specificity for which CAD EYE performed best.CONCLUSION Real-time use of AI4CRP was feasible.Objective confidence values provided by a CADx is novel and self-critical AI4CRP showed higher diagnostic performances compared to AI4CRP.