Artificial insemination: the state of the art

The history of research into artificial insemination (AI) is over two centuries old and its commercial application now spans 75 years. It is appropriate to reflect on the contribution of this powerful method of gene dispersal. AI remains as one of the most important assisted reproductive technologies. The three cornerstones for its application are: it is simple, economical and successful. The importance of AI will be challenged in the next few decades. The remarkable progress made in other assisted reproductive technologies does have the potential to rapidly generate offspring. The challenge for any of these reproductive technologies to attain widespread use is to match AI in being simple, economical and successful. This review aims at capturing the salient advances in AI, the comparisons with natural mating and other reproductive technologies, and, whether the future of AI will be challenged. It predicts what the new horizon looks like and the role that AI will play in the overall reproductive technologies landscape.     

Amberlite IRA 900 versus calcium alginate in immobilization of a novel,engineered β-fructofuranosidase for short-chain fructooligosaccharide synthesis from sucrose

The immobilization of β-fructofuranosidase for short-chain fructooligosaccharide (scFOS) synthesis holds the potential for a more efficient use of the biocatalyst. However, the choice of carrier and immobilization technique is a key to achieving that efficiency. In this study, calcium alginate (CA), Amberlite IRA 900 (AI900) and Dowex Marathon MSA (DMM) were tested as supports for immobilizing a novel engineered β-fructofuranosidase from Aspergillus japonicus for scFOS synthesis. Several immobilization parameters were estimated to ascertain the effectiveness of the carriers in immobilizing the enzyme. The performance of the immobilized biocatalysts are compared in terms of the yield of scFOS produced and reusability. The selection of carriers and reagents was motivated by the need to ensure safety of application in the production of food-grade products. The CA and AI900 both recorded impressive immobilization yields of 82 and 62%, respectively, while the DMM recorded 47%. Enzyme immobilizations on CA, AI900 and DMM showed activity recoveries of 23, 27, and 17%, respectively. The CA, AI900 immobilized and the free enzymes recorded their highest scFOS yields of 59, 53, and 61%, respectively. The AI900 immobilized enzyme produced a consistent scFOS yield and composition for 12 batch cycles but for the CA immobilized enzyme, only 6 batch cycles gave a consistent scFOS yield. In its first record of application in scFOS production, the AI900 anion exchange resin exhibited potential as an adequate carrier for industrial application with possible savings on cost of immobilization and reduced technical difficulty.     

Artificial intelligence and machine learning for medical imaging: A technology review

Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence of disruptive technical advances and impressive experimental results, notably in the field of image analysis and processing. In medicine, specialties where images are central, like radiology, pathology or oncology, have seized the opportunity and considerable efforts in research and development have been deployed to transfer the potential of AI to clinical applications. With AI becoming a more mainstream tool for typical medical imaging analysis tasks, such as diagnosis, segmentation, or classification, the key for a safe and efficient use of clinical AI applications relies, in part, on informed practitioners. The aim of this review is to present the basic technological pillars of AI, together with the state-of-the-art machine learning methods and their application to medical imaging. In addition, we discuss the new trends and future research directions. This will help the reader to understand how AI methods are now becoming an ubiquitous tool in any medical image analysis workflow and pave the way for the clinical implementation of AI-based solutions.     

Efficacy of cyhalothrin and lambdacyhalothrin against Boophilus microplus (Acari: Ixodidae).

A study was conducted to determine the efficacy of cyhalothrin and lambdacyhalothrin as a whole-body spray and lambdacyhalothrin as a pour-on application on cattle infested with Boophilus microplus (Canestrini). A laboratory bioassay was also done with both spray formulations. Cattle were infested with all parasitic life stages of B. microplus, then treated with 0.007 or 0.01% (AI) concentrations of cyhalothrin as a spray; 0.005, 0.007, or 0.01% (AI) concentrations of lambdacyhalothrin as a spray, or 1% (AI) lambdacyhalothrin as a pour-on. As determined by calculations of the index of reproduction (IR), the 0.007 and 0.01% (AI) cyhalothrin provided 92.4 and 97.3% control, respectively; the 0.005, 0.007, and 0.01% (AI) lambdacyhalothrin provided 92.4, 98.2 (average of two treatments) and 99.3% control, respectively; and the lambdacyhalothrin pour-on treatment provided < 50% control. Bioassay results indicated lambdacyhalothrin to be twice as effective as cyhalothrin against B. microplus.     

利用大肠杆菌高效表达人载脂蛋白AI及其性质分析

载脂蛋白AI(apolipoproteinAI,apoAI)是高密度脂蛋白HDL的主要组成成分 ,流行病学研究表明apoAI的含量决定血浆中HDL的高低 ,而HDL具有胆固醇逆向转运的功能 ,起到降低冠心病发生概率的作用。通过大肠杆菌表达系统来生产apoAI的蛋白原proapoAI,蛋白的表达形式为包涵体 ,通过疏水柱进行柱上复性。同时在proapoAI和apoAI之间设计一个酸水解位点 ,通过将蛋白原proapoAI进行酸水解来得到成熟蛋白apoAI。最终得到的成熟蛋白apoAI在结构分析和脂结合特性上都与天然的apoAI相似 ,从而为该蛋白的工业生产上提供了一个良好的基础。     

人工智能时代发酵优化与放大技术的机遇与挑战

人工智能(artificial intelligence, AI)技术正引发一场新的产业革命,其成功应用正从信息产业迅速渗透到各行各业。传统的发酵工程技术受到巨大挑战的同时更多地迎来了发展变革的机遇。首先,合成生物技术飞速发展使高性能菌株的可获得性及获取效率显著提升,对传统低效的发酵优化放大技术提出很大挑战,亟需对发酵优化放大技术进行升级,以满足高通量菌种性能验证及工艺开发能力的需求;其次,发酵装备技术的持续发展为高效发酵优化技术的进步奠定了良好基础,加之人工智能技术特别是数字孪生与知识图谱等技术的应用,将为传统发酵技术的颠覆性发展带来巨大推动力。本文分别从合成生物时代对发酵优化技术的挑战、发酵优化与放大的核心技术、高通量发酵装备技术、数据可视化技术、数字孪生及知识图谱等智能技术在发酵优化放大中的应用等几个方面进行综述,并对未来工业发酵优化技术的场景以及未来发酵技术对人才培养等提出的新要求进行了展望。     

Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy

PurposeTo perform a systematic review on the research on the application of artificial intelligence (AI) to imaging published in Italy and identify its fields of application, methods and results.Materials and MethodsA Pubmed search was conducted using terms Artificial Intelligence, Machine Learning, Deep learning, imaging, and Italy as affiliation, excluding reviews and papers outside time interval 2015–2020. In a second phase, participants of the working group AI4MP on Artificial Intelligence of the Italian Association of Physics in Medicine (AIFM) searched for papers on AI in imaging.ResultsThe Pubmed search produced 794 results. 168 studies were selected, of which 122 were from Pubmed search and 46 from the working group. The most used imaging modality was MRI (44%) followed by CT(12%) ad radiography/mammography (11%). The most common clinical indication were neurological diseases (29%) and diagnosis of cancer (25%). Classification was the most common task for AI (57%) followed by segmentation (16%). 65% of studies used machine learning and 35% used deep learning. We observed a rapid increase of research in Italy on artificial intelligence in the last 5 years, peaking at 155% from 2018 to 2019.ConclusionsWe are witnessing an unprecedented interest in AI applied to imaging in Italy, in a diversity of fields and imaging techniques. Further initiatives are needed to build common frameworks and databases, collaborations among different types of institutions, and guidelines for research on AI.     

小鼠初级听皮质神经元的强度调谐特性与机制分析

强度是声音的基本参数之一,听神经元的强度调谐在听觉信息处理方面具有重要意义．以往研究发现γ-氨基丁酸(γ-aminobutyric acid, GABA)能抑制性输入在强度调谐的形成过程中起重要作用,但对抑制性输入与局部神经回路之间的关系并不清楚．本实验通过在体细胞外电生理记录和神经药理学方法,分析了小鼠初级听皮质神经元的强度调谐特性,结果显示：单调型神经元在声刺激强度自中等强度增高时潜伏期缩短(P < 0.05)且发放持续时间延长(P < 0.05),非单调型神经元在声刺激强度自最佳强度增高时潜伏期不变且发放持续时间缩短(P < 0.01)．注射GABA能阻断剂荷包牡丹碱(bicuculline, Bic)后,39.3%的神经元强度调谐类型不变,42.9%的神经元非单调性减弱,17.9%的神经元非单调性增强．表明GABA能抑制并非是形成非单调性的唯一因素,兴奋性输入本身的非单调性和高阈值非GABA能抑制的激活也可能在其中发挥作用．推测由兴奋性和抑制性输入所构成的局部神经功能回路及其整合决定了听皮质神经元的强度调谐特性．     

樱桃根际促生细菌的筛选与鉴定

【目的】筛选樱桃[Cerasus pseudocerasus(Lindl.)G.Don]生物肥料中应用的优良菌株资源。【方法】通过保绿法和萝卜子叶增重法,结合定量检测细菌分离物产植物激素的能力,从樱桃根际土壤中筛选具有良好应用潜力的细菌分离物。利用盆栽试验,验证其促生效果。对促生效果较好的细菌分离物,进行形态学观察、生理生化测定、16S rRNA基因序列及系统发育树分析以确定其分类地位。【结果】筛选出4株具有良好应用潜力的细菌分离物,盆栽试验结果表明:AI5、AI21、PII17、PI7,尤其是PII17,显著提高樱桃根系及地上部生物量,对樱桃生长有明显的促进作用。分类鉴定结果显示:AI5、AI21为短小芽孢杆菌(Bacillus pumilus),PII17为假单胞菌属(Pseudomonas sp.),PI7为肠杆菌属(Enterobacter sp.)。【结论】AI5、AI21、PII17、PI7,尤其是PII17,对樱桃生长有明显的促进作用,在生物肥料的生产中具有广阔的应用前景。     

不同灌水施肥策略对土壤微生物量碳氮和酶活性的影响

根区局部灌溉形成一个土壤水分分布不均匀的环境,影响了土壤微生物量和酶活性。为探明这种影响,在2种灌水水平(正常灌水和轻度缺水)和2种有机无机N肥配施(单施无机N肥和有机无机N肥配施)下,以常规灌溉(CI)为对照,研究分根区交替灌溉(AI)和固定部分根区灌溉(FI)对土壤微生物量C(MBC)、微生物量N(MBN)和酶活性的影响。与CI相比,AI提高拔节期土壤MBC和抽雄期土壤脲酶活性,但是降低大喇叭口期土壤MBC以及拔节期和抽雄期土壤MBN和拔节期土壤脲酶活性;FI增加抽雄期土壤转化酶活性,但是降低大喇叭口期土壤MBC和可溶性碳(DOC)以及3个时期土壤MBN。与正常灌水相比,AI下轻度亏水增加拔节期和抽雄期土壤DOC,但是降低大喇叭口期土壤MBC和拔节期土壤MBN。与单施无机N肥相比,AI下有机无机N肥配施增加拔节期土壤DOC、MBN和过氧化氢酶活性,而FI下则降低大喇叭口期土壤MBC和转化酶活性。因此,在轻度缺水和有机无机氮配施条件下,分根区交替灌溉可以提高玉米拔节期土壤微生物量碳和可溶性碳。     

加气灌溉对不同施氮水平的设施甜瓜土壤CO2和N2O排放的影响

为探讨不同加气灌溉施氮模式下设施甜瓜土壤CO₂和N₂O排放的动态变化规律及其与土壤温度、湿度的关系,本研究采用密闭静态箱-气相色谱法对加气灌溉不同施氮水平下土壤CO₂和N₂O排放进行监测,并分析了加气灌溉对不同施氮量下土壤CO₂和N₂O排放的影响.试验采用加气灌溉(AI)和不加气灌溉(CK)两种灌溉方式,施氮量设不施氮(N₁)、传统施氮量的2/3(150 kg·hm^-2,N₂)和传统施氮量(225 kg·hm^-2,N₃)3个施氮水平.结果表明:加气灌溉土壤CO₂和N₂O排放量高于不加气灌溉处理,但是差异不显著;相同灌溉模式下,CO₂和N₂O排放量随施氮量的增加而显著增加,施氮量是土壤CO₂和N₂O排放的主要影响因素.加气灌溉条件下,不同施氮处理N₂O排放通量与土壤温度和湿度呈显著正相关,CO₂排放通量与土壤温度呈显著正相关.加气减氮处理在氮肥减少1/3的情况下,甜瓜产量提高了6.9%,温室气体排放引起的增温潜势值从9544.82 kg·hm^-2下降到9340.72 kg·hm^-2.综上,通过加气灌溉减少氮肥施用量来抑制农业生产系统中温室气体排放是可行的.     

加气灌溉对不同施氮水平的设施甜瓜土壤CO2和N2O排放的影响

为探讨不同加气灌溉施氮模式下设施甜瓜土壤CO₂和N₂O排放的动态变化规律及其与土壤温度、湿度的关系,本研究采用密闭静态箱-气相色谱法对加气灌溉不同施氮水平下土壤CO₂和N₂O排放进行监测,并分析了加气灌溉对不同施氮量下土壤CO₂和N₂O排放的影响.试验采用加气灌溉(AI)和不加气灌溉(CK)两种灌溉方式,施氮量设不施氮(N₁)、传统施氮量的2/3(150 kg·hm^-2,N₂)和传统施氮量(225 kg·hm^-2,N₃)3个施氮水平.结果表明:加气灌溉土壤CO₂和N₂O排放量高于不加气灌溉处理,但是差异不显著;相同灌溉模式下,CO₂和N₂O排放量随施氮量的增加而显著增加,施氮量是土壤CO₂和N₂O排放的主要影响因素.加气灌溉条件下,不同施氮处理N₂O排放通量与土壤温度和湿度呈显著正相关,CO₂排放通量与土壤温度呈显著正相关.加气减氮处理在氮肥减少1/3的情况下,甜瓜产量提高了6.9%,温室气体排放引起的增温潜势值从9544.82 kg·hm^-2下降到9340.72 kg·hm^-2.综上,通过加气灌溉减少氮肥施用量来抑制农业生产系统中温室气体排放是可行的.     

Can external quality control improve pig AI efficiency?

External quality control programmes carried out by central laboratories have been long established in human andrology with the aim of enhancing the accuracy and reproducibility of semen assessment. Compared to human, demands on boar semen assessment in AI stations are more complex, with the need both to identify boars with poor ejaculate quality and to monitor individual boar differences for semen storage. Additionally, appropriate assessment serves as a control instrument to ensure the security and efficiency of semen processing. Despite current limitations regarding the ability of sperm assays to estimate the potential fertility of males, it is evident that boar fertility is related to certain conventional semen tests, e.g. sperm morphology. In central studies carried out on stored semen from 11 AI stations, flow cytometric assessment of plasma and acrosome membrane integrity proved to be more sensitive in detecting sperm damage associated with ageing and temperature stress as compared to light microscopy. Membrane integrity of stored semen differed between AI stations indicating significant influences of semen processing on sperm quality. Thus external control of semen quality in reference laboratories may be useful to monitor the efficiency of internal semen quality control in individual AI stations, to identify males with lower semen quality and/or poor response to semen storage, and to verify the precision of sperm counting. The possibility that central laboratories with sufficient resources may be able to identify functionally different responding sperm subpopulations for better estimation of fertility is discussed. Ideally, external quality control schemes for AI stations would comprise application of validated tests with high relevance for fertility (including bacterial status), analysis of semen processing on the AI station, and training courses for laboratory personnel.     

Artificial insemination in marsupials

Assisted breeding technology (ART), including artificial insemination (AI), has the potential to advance the conservation and welfare of marsupials. Many of the challenges facing AI and ART for marsupials are shared with other wild species. However, the marsupial mode of reproduction and development also poses unique challenges and opportunities. For the vast majority of marsupials, there is a dearth of knowledge regarding basic reproductive biology to guide an AI strategy. For threatened or endangered species, only the most basic reproductive information is available in most cases, if at all. Artificial insemination has been used to produce viable young in two marsupial species, the koala and tammar wallaby. However, in these species the timing of ovulation can be predicted with considerably more confidence than in any other marsupial. In a limited number of other marsupials, such precise timing of ovulation has only been achieved using hormonal treatment leading to conception but not live young. A unique marsupial ART strategy which has been shown to have promise is cross-fostering; the transfer of pouch young of a threatened species to the pouches of foster mothers of a common related species as a means to increase productivity. For the foreseeable future, except for a few highly iconic or well studied species, there is unlikely to be sufficient reproductive information on which to base AI. However, if more generic approaches can be developed; such as ICSI (to generate embryos) and female synchronization (to provide oocyte donors or embryo recipients), then the prospects for broader application of AI/ART to marsupials are promising.     

禽流感病毒血凝素蛋白的结构、功能与表达

血凝素蛋白（HA）既是一种重要吸附蛋白,介导禽流感病毒吸附和穿入宿主细胞而发挥致病作用,也是一种良好的保护性抗原,对宿主抵抗禽流感起到了决定性保护作用。研究HA蛋白对揭示禽流感病毒的致病机理和免疫防治禽流感均具有重要意义。本文重点概述了HA蛋白的结构、功能和蛋白表达方面的研究进展,并对HA蛋白在禽流感疫苗中的应用进行了探讨。     

Laboratory and field evaluation of insect repellents as oviposition deterrents against the mosquito Aedes albopictus

Three experimental approaches were used to evaluate the oviposition deterrency of three insect repellents, AI3-35765, AI3-37220 (piperidine compounds), and the standard N,N-diethyl-3-methylbenzamide (deet) to the mosquito Aedes albopictus Skuse (Diptera: Culicidae). Against laboratory-reared Ae. albopictus gravid females, the EC50 values of AI3-37220, AI3-35765 and deet were 0.004%, 0.008% and 0.011% in laboratory cages and 0.004%, 0.01% and 0.009% in an outdoor screened cage. For a natural population of Ae. albopictus tested in the field, the EC50 values were determined as 0.004%, 0.008% and 0.001%, respectively. Ageing concentrations of 0.1% of each repellent provided >50% effective oviposition deterrency against the laboratory population of Ae. albopictus for 13 days in laboratory cages, for 15 days in the outdoor cage, and for 21 days against field population of Ae. albopictus in Florida. These topical skin repellents are effective oviposition deterrents for Ae. albopictus when employed at relatively low application rates.     

孕中晚期胎儿主动脉弓狭窄的超声诊断参数分析及其影响因素分析

摘要 目的：探究孕中晚期胎儿主动脉弓狭窄的超声诊断参数分析,并就超声诊断参数对孕中晚期胎儿主动脉弓狭窄的影响因素开展分析。方法：选择2020年7月至2021年7月于我院就诊后被确诊为孕中晚期主动脉弓狭窄的40例胎儿为狭窄组,另取同期体格检查正常的40例胎儿为对照组,以胎儿出生后超声心动图检测或尸检结果为金标准,比较两组胎儿超声指标Z-分数（AI Z-score）、升主动脉Z-分数（AO Z-score）、主动脉峡部/升主动脉（AI/AO）差异,分别绘制AI Z-score、AO Z-score以及AI/AO对孕中晚期胎儿主动脉弓狭窄的诊断ROC曲线,并计算其曲线下面积（AUC）,最后采用Logistic回归分析的方式计算孕中晚期胎儿主动脉弓狭窄影响因素。结果：（1）窄缩组胎儿的超声参数AI Z-score、AO Z-score以及AI/AO均明显低于对照组（P<0.05）;（2）AI/AO为孕中晚期胎儿主动脉弓狭窄的危险因素（P<0.05）;（3）AI Z-score、AO Z-score、AI/AO以及联合检测对胎儿主动脉弓狭窄的诊断AUC分别为0.801（95% CI=0.691-0.910,P<0.001）、0.835（95% CI=0.739-0.932,P<0.001）、0.843（95% CI=0.757-0.929,P<0.001）、0.920（95% CI=0.865-0.975,P<0.001）,截断值分别为-1.64、-1.47和0.535,诊断灵敏度和特异度分别为72.50%和72.50%、77.50%和77.50%、75.00%和80.00%、85.00%和82.50%。结论：超声诊断对孕中晚期胎儿主动脉弓狭窄具有较好的诊断价值,其指标AI Z-score、AO Z-score、AI/AO能够量化分析孕中晚期胎儿主动脉弓狭窄风险,可以考虑将其应用于临床中。     

Dynamic QoS/QoE-aware reliable service composition framework for edge intelligence

Edge intelligence has become popular recently since it brings smartness and copes with some shortcomings of conventional technologies such as cloud computing, Internet of Things (IoT), and centralized AI adoptions. However, although utilizing edge intelligence contributes to providing smart systems such as automated driving systems, smart cities, and connected healthcare systems, it is not free from limitations. There exist various challenges in integrating AI and edge computing, one of which is addressed in this paper. Our main focus is to handle the adoption of AI methods on resource-constrained edge devices. In this regard, we introduce the concept of Edge devices as a Service (EdaaS) and propose a quality of service (QoS) and quality of experience (QoE)-aware dynamic and reliable framework for AI subtasks composition. The proposed framework is evaluated utilizing three well-known meta-heuristics in terms of various metrics for a connected healthcare application scenario. The experimental results confirm the applicability of the proposed framework. Moreover, the results reveal that black widow optimization (BWO) can handle the issue more efficiently compared to particle swarm optimization (PSO) and simulated annealing (SA). The overall efficiency of BWO over PSO is 95%, and BWO outperforms SA with 100% efficiency. It means that BWO prevails SA and PSO in all and 95% of the experiments, respectively.

     

AI-based approach to automatic sleep classification

The primary goal of this paper is to introduce the potential of artificial intelligence (AI) methods to researchers in sleep classification. AI provides learning procedures for the construction of a sleep classifier, prescribing how to combine the observed parameters and how to derive the corresponding decision thresholds. A case study reporting a successful application of an automatic induction of decision trees and of a learning vector quantizer to this domain is presented. Received: 24 May 1993/Accepted in revised form: 8 September 1993     

Time dependent influence of etonogestrel on the caspase-3 immunoreactivity and apoptotic indexes of rat uterus and ovaries

Apoptosis is necessary for the balance between cell proliferation and loss. Thirty-six Wistar-Albino rats were subjected to investigate apoptotic effect of widely used implantable progestins on ovarian and uterine tissues. Rats were divided into 6 groups. In the first five groups, we applied etonogestrel (IMP) subcutaneous implants (n = 30). The rats in groups were sacrificed sequentially every 10 days after application. The rats in the last group (n = 6) were accepted as controls. Apoptotic index (AI) values and Caspase-3 immunoreactivities of ovaries and uterus were recorded. In IMP groups, AI and Hscore values in stroma and glandular epithelium of uterus, granulosa and teca-lutein cells of the ovary increased with the longer progesterone exposure. Increase in AI and Hscore values were more prominent after 30 days of exposure for teca-lutein cells of ovary. Progestins increased apoptosis in ovaries and uterus by the longer exposure. Apoptosis increased in ovaries by chronic progesterone exposure. The apoptotic effect of progestin on endometrium is clear but long-term systemic application may lead to alterations in ovarian physiology. We evaluated time dependent apoptotic effect of etonogestrel on reproductive physiology and discussed progestins effect from another point of view in this study.