Mouse models in male fertility research

Limited knowledge of the genetic causes of male infertility has resulted in few treatment and targeted therapeutic options. Although the ideal approach to identify infertility causing mutations is to conduct studies in the human population, this approach has progressed slowly due to the limitations described herein. Given the complexity of male fertility, the entire process cannot be modeled in vitro. As such, animal models, in particular mouse models, provide a valuable alternative for gene identification and experimentation. Since the introduction of molecular biology and recent advances in animal model production, there has been a substantial acceleration in the identification and characterization of genes associated with many diseases, including infertility. Three major types of mouse models are commonly used in biomedical research, including knockoutJknockin/gene-trapped, transgenic and chemical-induced point mutant mice. Using these mouse models, over 400 genes essential for male fertility have been revealed. It has, however, been estimated that thousands of genes are involved in the regulation of the complex process of male fertility, as many such genes remain to be characterized. The current review is by no means a comprehensive list of these mouse models, rather it contains examples of how mouse models have advanced our knowledge of post-natal germ cell development and male fertility regulation.

Phosphorus limitation on CO_(2)fertilization effect in tropical forests informed by a coupled biogeochemical model

Tropical forests store more than half of the world's terrestrial carbon(C)pool and account for one-third of global net primary productivity(NPP).Many terrestrial biosphere models(TBMs)estimate increased productivity in tropical forests throughout the 21st century due to CO_(2)fertilization.However,phosphorus(P)liaitations on vegetation photosynthesis and productivity could significantly reduce the CO_(2)fertilization effect.Here,we used a carbon-nitrogen-phosphorus coupled model(Dynamic Land Ecosystem Model;DLEM-CNP)with heterogeneous maximum carboxylation rates to examine how P limitation has affected C fluxes in tropical forests during1860-2018.Our model results showed that the inclusion of the P processes enhanced model performance in simulating ecosystem productivity.We further compared the simulations from DLEM-CNP,DLEM-CN,and DLEMC and the results showed that the inclusion of P processes reduced the CO_(2)fertilization effect on gross primary production(GPP)by 25%and 45%,and net ecosystem production(NEP)by 28%and 41%,respectively,relative to CN-only and C-on ly models.From the 1860s to the 2010s,the DLEM-CNP estimated that in tropical forests GPP increased by 17%,plant respiration(Ra)increased by 18%,ecosystem respiration(Rh)increased by 13%,NEP increased by 121%per unit area,respectively.Additionally,factorial experiments with DLEM-CNP showed that the enhanced NPP benefiting from the CO_(2) fertilization effect had been offset by 135%due to deforestation from the 1860s to the 2010s.Our study highlights the importance of P limitation on the C cycle and the weakened CO_(2)fertilization effect resulting from P limitation in tropical forests.

THE DYNAMICS OF FERTILITY IN C-K MODEL WITH ENDOGENOUS FERTILITY

Based on the Cass-Koopmans Model with endogenous fertility given in the paper [1-4], the fertility dynamics is discussed in this paper. It is proved that the first quadrant of the k,c plane is separated into two parts by a increasingly differentiable curve. The fertility increases with time on the upper half and decreases with time on the lower half. The fertility decreases along one arm of the economic growth path on which the per capita capital and per consumption increase and increases along the other arm of the economic growth path on which the per capita capital and per person consumption decrease under the condition 0 <θ≤α. This confirms the empirical finds that negative relationship between the economic growth and population growth.

Modelling fertility:an application of count regression models

Often the lifecycle data occur as count of the vital events and are recorded as integers.The purpose of this article is to model the fertility behavior based on religious,educational,economic,and occupational characteristics.The responses of classified groups according to these determinants are examined for significant influence on fertility using Poisson regression model(PRM) based on the National Family Health Survey-3 dataset.The observed and predicted probabilities under PRM indicate modal value of two children for the Poisson distribution modeled data.Presence of dominance of two child in the data motivates the authors to adopt multinomial regression model(MRM) in order to link fertility with various socioeconomic indicators responsible for fertility variation.Choice of the explanatory factors is limited to the availability of data.Trends and patterns of preference for birth counts suggest that religion,caste,wealth,female education,and occupation are the dominant factors shaping the observed birth process.Empirical analysis suggests that both the models used in the study perform similarly on the sample data.However,fitting of MRM by taking birth count of two as comparison category shows improved Akaike information criterion and consistent Akaike information criterion values.Current work contributes to the existing literature as it attempts to provide more insight into the determinants of Indian fertility using Poisson and MRM.

SOME RESULTS ABOUT RCK MODEL WITH ENDOGENOUSE FERTILITY

In this paper, incorporating the fertility in the utility function and the production function, an improved Ramsey-Cass-Koopmans(RCK) model with endogenous fertility is obtained. In this model, the fertility can be expressed as a function of per capita capital and per capital consumption. It has been proved that at least one equilibrium point exists and the equilibrium point is unique under a condition. The author discusses the possibility of existing multiple equilibria, their geometrical relationship and explains the economic sense of the main results.

A RCK Model with Endogenous Fertility and Exogenous Technological Change

The technological change as an exogenous variable is introduced into the RCK model with endogenous fertility in this paper. It is proved that the model has at least a nonzero steady state and the nonzero steady state is unique when the parameters satisfies some conditions. By phrase protrait analysis, the unique nonzero steady state is saddle and the economy has a unique optimal growth path. The results obtained implies that the relationship between the technological change and population growth rate determinated by the economic structure and the parental ethies. For the economy in which the parents is selfish, promoting the technological change rate decreases the fertility at the steady state. On the other hand, for the economy in which the parents is less selfish, the fertility increases as the technological change rate increases.

An Improved Cass-Koopmans Model with Endogenous Fertility under the CES Production Technology

Under the CES production technology, an improved Cass Coopmans model with solvable endogenous fertility is given. We prove that there are multiple growth paths and multiple steady states when CES 0<σ<1 and the technology level is high enough; the growth path and the steady state is unique when σ>1 and the ratio of capital is smaller than a constant. So, the dynamic system which describes the model undergoes a bifurcation when σ=1 . We discuss the economic sense of the main results we give.

Establishment of a male fertility prediction model with sperm RNA markers in pigs as a translational animal model

Background:Male infertility is an important issue that causes low production in the animal industry.To solve the male fertility crisis in the animal industry,the prediction of sperm quality is the most important step.Sperm RNA is the potential marker for male fertility prediction.We hypothesized that the expression of functional genes related to fertilization will be the best target for male fertility prediction markers.To investigate optimum male fertility prediction marker,we compared target genes expression level and a wide range of field data acquired from artificial insemination of boar semen.Results:Among the genes related to acrosomal vesicle exocytosis and sperm–oocyte fusion,equatorin(EQTN),zona pellucida sperm-binding protein 4(ZP4),and sperm acrosome membrane-associated protein 3 exhibited high accuracy(70%,90%,and 70%,respectively)as markers to evaluate male fertility.Combinations of EQTN-ZP4,ZP4-protein unc-13 homolog B,and ZP4-regulating synaptic membrane exocytosis protein 1(RIMS1)showed the highest prediction value,and all these markers are involved in the acrosome reaction.Conclusion:The EQTN-ZP4 model was efficient in clustering the high-fertility group and may be useful for selection of animal that has superior fertility in the livestock industry.Compared to the EQTN-ZP4 model,the ZP4-RIMS1 model was more efficient in clustering the low-fertility group and may be useful in the diagnosis of male infertility in humans and other animals.The appointed translational animal model and established biomarker combination can be widely used in various scientific fields such as biomedical science.

A Simulating Model of Fertility Policy and Population Trends in China

Chinad s population policy and family planning programme have focused their attention on.a decline of the fertility rate.The Wan-Xi-Shao policy(i.e..the policy ofde ferred,spaced but fewer births)practised in the 1970s had brought about a rapid decline of the fertility leve1 in the coun-try.As aresult.the total fertility rate(TFR)of China's pop-ulation reduced from5.81 in1970 t 2.75 in 1979.Beginning from the late 1970s and early 1980s,the present family plan-ning policy,which encourages women of dhildbearing age to have only one child.has cont ributed to a continuous decline of the fertility rate。with TFR dropped to below the replacement level from 1990 to 1995.

A Hurdle Negative Binomial Regression Model for Non-Marital Fertility in Namibia

The rise of non-marital fertility, which seems to defy the Bongaarts model by decoupling marriage from fertility, has become a subject of interest in both the developed and developing world. Consequences of non-marital fertility are mostly negative particularly in developing countries. In Namibia, although premarital childbearing has been reported to be high and increasing, no studies have explicitly analyzed factors influencing non-marital fertility. This paper uses data from the 2006/7 Namibia DHS to establish the determinants of non-marital fertility among women by applying a two-part model, with one part to describe the presence of non-marital birth and the other part to explain its intensity （number of children born）. Using the number of children ever born as an outcome, we explored various count data models. Based on the Voung statistics model comparison, we settled for the Hurdle logit Negative Binomial regression to model the number of non-marital births. Non-marital fertility in Namibia is associated with the age, with young women likely to have lower fertility compared to older women. Women with secondary or higher education had lower fertility compared those with no formal education. Findings also show that rural women higher fertility propensity compared to their urban counterparts even though there was no significant difference in fertility intensity. With regard to socio-economic status, fertility intensity decreased as the women got richer. Intervention efforts should focus on promoting education among girls and women especially in rural areas to improve their socio-economic status, reduce teenage pregnancy and non-marital fertility.

Effect Models of Nitrogen,Phosphorus and Potassium Fertilizer Formulation in Banana

[Objective] The aim was to modify the application amount of N,P and K fertilizer so as to provide a reference for establishing balanced fertilization index system of banana.[Method]The N,P and K fertilizer ＂3414＂ test was carried out on banana,and then regression analysis was performed on the fertilizer effect.Ternary quadratic,binary quadric and one-variable quadratic regression equations for the fertilizer effect on the banana yield were constructed.[Result]Suitable amount of N,P and K fertilizer had significant yield improving effect,whereas overdose of fertilizer application led to decreasing of utilization rate of fertilizer.Therefore,suitable amount of N,P and K fertilizer should be selected in production.It could be concluded that one-variable quadratic regression equations was the best model to calculate the suitable fertilizer amount.The best yield range of banana in the tested field was 44.193-45.904 t/hm2,while the corresponding optimum application amount of N,P2O5 and K2O was 795.1,262.3 and 1 236.9 kg/hm2 respectively,and the ratio among nitrogen,phosphorus and potassium are 1∶0.33∶1.55.[Conclusion]The result in this study could provide references for the soil types similar to the tested field.

Optimized Allocation Model for Regional Agricultural Fertilizer Resources in Southern Xinjiang from the Perspective of Sustainable Development

[Objective] This study was to establish an optimized model for the allocation of agricultural fertilizer resources in Southern Xinjiang from the perspective of sustainable development.[Method] An optimized model for the allocation of agricultural fertilizer resources was established based on their allocation structure.Combined with the actual agricultural production in Aksu areas of Southern Xinjiang,by establishing a rational evaluation index system,under the premise of considering the planting area constraints,the total water resources constraints and the security constraints of food production,we established the empirical optimal allocation model of the regional agricultural fertilizer resources in Aksu area of Southern Xinjiang.Moreover,we solved the model by using the search algorithm of computer and lingo programming.[Result] The increased economic benefit was near to 1.8 billion Yuan by adopting the optimal allocation methods,with a relative increment of about 34.4%.[Conclusion] Our results provided theoretical basis for achieving the sustainable development of agricultural economy in Southern Xinjiang.

Farmers' Willingness on Organic Fertilizer Application Based on Logit Model and Influencing Factors——A case of Shandong Province

[Objective] The matter of chemical fertilizer being overused but organic fertilizer being deficiently used causes environment pollution and soil fertility degradation and holds back agricultural sustainable development in China at present.[Method] A survey of 200 farmers selected from Shandong province was conducted in 2008 to identify the factors influencing farmers willingness to use organic fertilizer.[Result] Logit model results showed that the proportion of non-farm income in total income,awareness of...

Study on Optimum Fertilization Model of Potato Intercropped with Sugarcane

[Objective] The paper was to study the effects of different ratios of N, P and K on yield of potato intercropped with sugarcane in Lateritic red earth area of Guangxi, and seek the best N, P and K ratio for nutrition model of potato inter- cropped with sugarcane. [Method]Two field experiments adopted the optimum com- pound design （311-A） were conducted in Long＇an County of Guangxi Province in 2011 and 2012, respectively. The polynomial regression models of fertilizer applica- tion and quadratic of three factors were established by SAS statistical analysis soft- ware, and optimum nutrient simulation models of potato were obtained by computer processing. [Result] The combined application of low nitrogen and mid-high potassi- um and phosphorus fertilizer contributed to higher potato yield in experimental condi- tion. The regression model of potato yield （Yll and Y12） and dosage of N（X1）, P （X2）, K（X3） were established by using SAS statistical analysis software, in 2011 and 2012, respectively. They were Y11 =14 725.28 -415.39X1 ＋741.99X2 ＋607.83）（3-447.92X1X2- 144.09X1X3 -405.83X2X3 -267.82X1^2-795.67X2^2 -642.10X3^2, R =0.927 2; and Y12 =14 342.60 -896.25X1 ＋548.62X2 ＋925.51 X3 ＋67.81 X1X2 ＋531.60X1X3 -99.00X2X3 -904.00X1^2 - 1121.36X2^2-596.64X3^2,R=0.926 6. The regression mathematics model of potato yields preferably fit with actual situation in the locality, and have higher practical value, so it could be used for fertilizer decision and forecast. Using the computer to carry on the optimization, the N, P and K dosage of the best potato yield intercropped with sugarcane was obtained. The dosage of N, P2O5, K2O were 108.8-140.6, 172.5-204.4 and 285.9 kg/hm2, respectively. [Conclusion] The best N, P and K ratio of potato yield intercropped with sugarcane was 1：（1.23-1.68）：（2.03-2.63）.

Establishment and Application of Fertilization Model for Wheat Interplanted with Cotton in Jianghan Plain

3414 field experiment （including three nutrient elements at four gradient levels, a total of 14 unrepeated incomplete treatments） was designed to study the fertilization measures for wheat interplanted with cotton in Qianjiang City, Hubei Province. Fertilizer model for wheat interplanted with cotton in Jianghan Plain was finally established, based on which the soil nutrient indices in wheat-cotton inter- planting field were screened; and optimal nitrogen, phosphorus and potassium appli- cation for wheat was put forward as 130-210 kg/hm2 N, 40-70 kg/hm2 P2O5 and 40-60 kg/hm2 K2O.

Basic Soil Productivity of Spring Maize in Black Soil Under Long-Term Fertilization Based on DSSAT Model

Increasing basic farmland soil productivity has significance in reducing fertilizer application and maintaining high yield of crops. In this study, we defined that the basic soil productivity （BSP） is the production capacity of a farmland soil with its own physical and chemical properties for a specific crop season under local environment and field management. Based on 22-yr （1990-2011） long-term experimental data on black soil （Typic hapludoll） in Gongzhuling, Jilin Province, Northeast China, the decision support system for an agro-technology transfer （DSSAT）-CERES-Maize model was applied to simulate the yield by BSP of spring maize （Zea mays L.） to examine the effects of long-term fertilization on changes of BSP and explore the mechanisms of BSP increasing. Five treatments were examined： （1） no-fertilization control （control）; （2） chemical nitrogen, phosphorus, and potassium （NPK）; （3） NPK plus farmyard manure （NPKM）; （4） 1.5 time of NPKM （1.5NPKM） and （5） NPK plus straw （NPKS）. Results showed that after 22-yr fertilization, the yield by BSP of spring maize significantly increased 78.0, 101.2, and 69.4% under the NPKM, 1.5NPKM and NPKS, respectively, compared to the initial value （in 1992）, but not significant under NPK （26.9% increase） and the control （8.9% decrease）. The contribution percentage of BSP showed a significant rising trend （P〈0.05） under 1.5NPKM. The average contribution percentage of BSP among fertilizations ranged from 74.4 to 84.7%, and ranked as 1.5NPKM〉NPKM〉NPK〉NPKS, indicating that organic manure combined with chemical fertilizers （I.5NPKM and NPKM） could more effectively increase BSP compared with the inorganic fertilizer application alone （NPK） in the black soil. This study showed that soil organic matter （SOM） was the key factor among various fertility factors that could affect BSP in the black soil, and total N, total P and/or available P also played important role in BSP increasing. Compared with the chemical fertilization, a balanced chemical plus manure or straw fertilization （NPKM or NPKS） not only increased the concentrations of soil nutrient, but also improved the soil physical properties, and structure and diversity of soil microbial population, resulting in an iincrease of BSP. We recommend that a balanced chemical plus manure or straw fertilization （NPKM or NPKS） should be the fertilization practices to enhance spring maize yield and improve BSP in the black soil of Northeast China.

A Dynamic Knowledge Model for Nitrogen Fertilizationin Wheat Management

By analyzing and extracting the research progress on nitrogen fertilization in wheat, a dynamic knowledge model for management decision-making on total nitrogen rate, ratios of organic to inorganic and of basal to dressing nitrogen under different environments and cultivars in wheat was developed with principle of nutrient balance and by integrating the quantitative effects of grain yield and quality targets, soil characters, variety traits and water management levels. Case studies on the nitrogen fertilization model with the data sets of different eco-sites, cultivars, soil fertility levels, grain yield and quality targets and water management levels indicate a good performance of the model system in decision-making and wide applicability.

Using fuzzy-AHP and parametric technique to assess soil fertility status in Northeast of Iran

A good understanding of the levels and distribution patterns of soil properties and/or quality indicators is a prerequisite for developing sustainable agricultural land management programs. Traditional assessments of these parameters of soil fertility status are somewhat costly, in both economics and time aspects. Different modelling techniques have been proposed as a useful tool for determination of soil quality indicators and development of soil fertility maps, but to what extent these results are reliable remains under-quantified in many regions worldwide. To address this uncertainty, Fuzzy-Analytical Hierarchy Process(Fuzzy-AHP) and Parametric analyses were conducted to ascertain the soil fertility status of a semiarid region in the Northeast of Iran for some selected crops: alfalfa, corn silage, potato, sugar beet, tomato and wheat. The Fuzzy-AHP and Parametric techniques using soil suitability indices were estimated for each crop and each soil delineation was achieved by Ordinary Kriging. The Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS) was used as a compensatory method to allow tradeoffs among the selected criteria. Our results demonstrated that from the Fuzzy-AHP analysis, the soil fertility indices ranged from moderate to high for production of alfalfa;from low to high for production of corn silage and sugar beet;moderate to high for production of potato and tomato;and from low to moderate for production of wheat. However, the parametric analysis showed soil fertility classes ranging from very low to high for production of all the selected crops. High correlations were also observed between soil fertility indices predicted by both models. Similarly, the capacities of both models to predict soil fertility status for production of the selected crops were also highly correlated. The preference for the cultivation of the selected crops based on the Fuzzy-AHP analysis was sugar beet > corn silage > wheat > alfalfa > tomato > potato. On the other hand, using Parametric techniques, the crops preferences for cultivation ranked as corn silage > wheat > alfalfa > sugar beet > tomato > potato. We concluded that the findings would help to develop sustainable plans of cultivation based on patterns related to soil fertility classes depending on each crop’s requirement.

MIMO Soft-sensor Model of Nutrient Content for Compound Fertil- izer Based on Hybrid Modeling Technique

In compound fertilizer production, several quality variables need to be monitored and controlled simultaneously. It is very diifficult to measure these variables on-line by existing instruments and sensors. So, soft-sensor technique becomes an indispensable method to implement real-time quality control. In this article, a new model of multi-inputs multi-outputs （MIMO） soft-sensor, which is constructed based on hybrid modeling technique, is proposed for these interactional variables. Data-driven modeling method and simplified first principle modelingmethod are combined in this model. Data-driven modeling method based on limited memory partial least squares（LM-PLS） al.gorithm is used to build soft-senor models for some secondary variables.then, the simplified first principle model is used to compute three primary variables on line. The proposed model has been used in practicalprocess; the results indicate that the proposed model is precise and efficient, and it is possible to realize on line quality control for compound fertilizer process.

Evaluation of the CROPGRO-Peanut model in simulating appropriate sowing date and phosphorus fertilizer application rate for peanut in a subtropical region of eastern India

Projected changes in weather parameters, mainly temperature and rainfall, have already started to show their effect on agricultural production. To cope with the changing scenarios, adoption of appropriate management strategies is of paramount importance. A study was undertaken to evaluate the most appropriate combination of sowing date and phosphorus fertilization level for peanut crops grown in sandy loam soil in a subhumid region of eastern India. Field experiments were conducted during the summer seasons of 2012 and 2013 on peanut crops at the farm of the Indian Institute of Technology, Kharagpur. The DSSAT v4.5 CROPGRO-Peanut model was used to predict the phenology, growth, and yield of peanut crop under combinations of four sowing dates and four phosphorus fertilization levels. The model was calibrated with a 2012 dataset of growth, phenology, and yield parameters for estimating the genetic coefficients of cultivar TMV-2 and was validated with a 2013 dataset of the same parameters. Simulations of pod yield and other yield parameters using the calibrated model were found to be quite accurate. The model was able to reasonably simulate pod yield and final biomass with low normalized root mean square error (RMSE_n), low absolute root mean square error (RMSE_a) and high coefficient of determination (R^2> 0.7) over a wide range of sowing dates and different phosphorus fertilization levels sensitivity analysis indicated that sowing from the second week of January to the end of February with 30–50 kg P_2O_5 ha^(-1)would give the highest pod yield.