The persistently high and stalled total fertility in Sub-Saharan Africa, including in Nigeria, calls for new efforts towards fertility reduction. Most efforts on fertility desire in sub-Saharan Africa have focused either on individual men or women with little focus on couples as a unit of analysis. Moreover, the influences of different types of marriages in which couples reproduce have not been adequately explored. Therefore, this study examined fertility desires among couples in Nigeria.This paper used data from the Nigeria Demographic and Health Survey (NDHS) of 2018 to assess fertility desire by marriage type among couples in Nigeria. In addition, the association between fertility desire and disparity in couples’ educational attainment, place of residence, region, religion, occupation, wealth status, children ever born and contraceptive use were considered. The participants consisted of 6813 couples aged between 15–49 years. Couples’ characteristics were reported using frequency and percentage distribution tables. Descriptive and logistic regression analyses were conducted.Overall, the study revealed that 73.8% of couples were in monogamous relationships while 26.2% were in polygynous relationships. The mean ideal number of children for men and women were 7.2 and 6.1, respectively. Also, 49.3% of the couples reported husbands desired more children, 43.9% claimed wives desired more children, while 6.8% indicated equal number of desired children among wives and husbands. The results of binary logistic regression showed that couples in polygynous relationships were 4.3 times as likely to desire more children, compared to couples in monogamous relationships . Couples in polygynous relationships wanted as many as four times the number of children desired by couples in monogamous relationships. Fertility desire was significantly higher among couples who indicated the following: either was using contraceptives , both were not using contraceptives , lived in North East  and North West , both were not working  and were adherents of Islam .These findings reflect the role of region, use of contraceptives, work status and religion in the fertility desire of couples. Implementing programmes and policies on sexual education and reproductive rights of couples and individuals may reduce high fertility desire and its adverse consequences, such as child and maternal morbidity and mortality in Nigeria. The total fertility rate in West African countries remains high despite the development and implementation of several interventions. The literature identifies significant factors relating to fertility desires and subsequent population growth at individual, household and community levels. Nevertheless, the high and stalled total fertility rate of Nigeria at 5.3 calls for new approaches to affect fertility. Marital fertility constitutes a substantial part of total fertility in Nigeria. Previous studies mostly focused on the fertility desires of men and women. Motivated by an emerging interest in fertility intentions, the study examined fertility preferences among monogamous and polygynous couples in Nigeria. Data for the study were retrieved from Nigeria Demographic and Health Survey (NDHS) of 2018. A total sample of 6813 couples between 15 and 49 years of age was used in the study. Analyses were done using frequency and percentage distribution tables and a logistic regression model. Couples in polygynous relationships wanted about four times the number of children desired by couples in monogamous relationships. There were disparities in socio-demographic characteristics of couples and contraceptive use by type of marriage. Factors influencing the desire for more children among couples were work status, region, religion and contraceptive use. Existing interventions should take these factors into consideration.Achievement of Sustainable Development Goals (SDGs), especially goals one , three , four  and five  might be a mirage without conscious efforts on the part of many developing countries to reduce population growth –3. RapidGenerally, many developing countries of the world have witnessed development in their demographic transition. This has shown in the tremendous reduction in fertility and mortality rates over the last few decades –6. HowevIntroduced in 1988, the National Policy on Population for Development, Unity, Progress and Self-Reliance set the following targets for one of its goals: ‘To achieve lower population growth rates, through reduction of birth rates by voluntary fertility regulation methods that are compatible with the attainment of economic and social goals of the nation.' The policy focused on individuals and couples in monogamous and polygynous families. This focus was necessary because marital fertility constituted a substantial part of the fertility in Nigeria. Moreover, this was not unconnected with the fertility desire of the monogamous and polygynous families. The total fertility rate was 6.0 in 1990. It was 5.7 in 2003, about fifteen years after the policy on population was introduced. The policy was revised and replaced in 2005 with the National Policy on Population for Sustainable Development, which set the following targets for one of its goals: ‘Progress towards a complete demographic transition to a reasonable growth in birth rates and a low death rate.' Three years later (in 2008), the total fertility rate remained 5.7. Eight years later (in 2013), the total fertility rate reduced to 5.5, a rate that was sustained for several years of population policies. The 2018 NDHS released in 2019 put the figure at 5.3 [This has provoked a series of studies on the significant predictors of fertility in the country. Many empirical biosocial studies have revealed significant individual, household, kinship and community determinants of fertility rates in sub-Saharan Africa and Nigeria, in particular . ImportaResearch has shown that most births are within marital unions , 8. ConsNigeria, a country endowed with natural resources, can enjoy demographic dividend. This includes couples with other achievements, decline in mortality rates, increase in productivity of the working population, quality of education, adequate nutrition and access to sexual and reproductive health and rights. Also, there have been significant reductions in fertility and there are still conscious efforts being made. The reduction in fertility rate in Nigeria may reduce population growth and pave way for socio-economic development in the long run. Demographic dividend may facilitate economic growth and also enhance the possibility of quality education, good health and adequate nutrition. Change in population age structure due to a higher proportion of working people in the total population will increase the potential for economic growth and development.This study is underpinned by the polygyny-fertility hypothesis; this hypothesis associates reduced fertility with polygyny. Theoretically, studies on the polygyny-fertility hypothesis showed mixed results. Many of the studies explained that fertility was lower in polygynous marriages compared to monogamous marriages and that inconsistency occurred due to differences in fertility by wife-order, number and aggregation of fertility among women in a polygynous marriage , 24. On Given the emerging interest in the study of fertility intention among couples in developing countries, this study examined the extent to which couples in marriage types desire for children and the factors associated with it in Nigeria. Previous attempts at explaining fertility desire focused mainly on women or men , 16, 19.Data for this study were derived from the 2018 NDHS couples’ recode dataset. It was a cross-sectional, comparable and nationally representative survey that employed a three-stage sampling technique. Taking into consideration the probability proportional to enumeration area size, 1400 Enumeration Areas (EAs) were selected. In all selected EAs, a household listing was done and the lists of households were used as a sampling frame. Nigeria was divided into clusters based on the 2006 Enumeration Areas (EAs) census frame and demarcation. In each cluster, 30 households were selected randomly to arrive at a representative sample of 42,000 households. Women in the 15–49 age range who were permanent residents or visitors in the household the night before the survey were considered eligible to participate in the interview.The survey involved three different questionnaires. These were the household questionnaire, women’s questionnaire and men’s questionnaire. Also, a sub-sample of half of the men in the 15–49 age range in selected households was also interviewed . ObjectiFertility desire was the outcome or dependent variable. It had three categories: ‘equal desire,' ‘husbands desire more’ and ‘wives desire more.' It was further reduced to two categories  and the correlation between independent variables was less than 0.7 . A binarTable The percentage distribution of the couples by wealth status revealed that 39.8% belonged to the poor category, 19.8% belonged to the middle class category, while 40.4% belonged to the rich category. Fertility desires by couples’ characteristics were also examined. As also revealed in Table This section presents the results of multivariate analysis Table . The relP < 0.001) in a polygynous marriage type relative to monogamy. The model also revealed positive, statistically significant odds ratio for more desire for children by husbands among couples who were not using contraceptive , either was using contraceptive  and among couples who were not both working . In addition, this study found statistically significant odds ratio for more desire for children by husbands among the couples in North East , North West  and the couples who were adherents of Islam .The model revealed the adjusted odds ratios of the selected independent variables on fertility desire. This model revealed a positive, statistically significant, higher odds ratio for more desire for children by husbands  which indicated that Nigeria was noted for polygyny . There wThe study also indicated that residence in North East and North West regions were related to fertility desire of couples. The Northern part of Nigeria had been noted for high fertility desire and this phenomenon may be associated with Islamic religion and early marriage which encourages polygyny and high fertility, respectively. Fertility intention was found to be associated with the use of contraceptives among couples. The desire for children was higher among couples who were not using contraceptives . Many coThe major strength of this study is the use of 2018 nationally representative Nigeria Demographic and Health Survey datasets collected through a consistent methodology. This makes the findings of the study generalizable. However, this analysis has some drawbacks. Prominently, the analysis utilized cross-sectional data; hence, only associations and no causal relationships are established. Since the survey was self-reported, there are the possibilities of recall and social acceptability biases. Another limitation of the study is that fertility desires of husbands as reported by wives were used for analysis because a fertility report of the husbands was not available. Also, reports of husbands on children ever born were used due to the polygynous nature of many families and the fact that a woman might report her own children ever born rather than that of the family. In addition, it could be that couples were in a polygynous relationship to have more children. There could be some limitations as regards to the accuracy and quality of educational level of respondents, for example, on the part of respondents with little or no formal education.The study revealed the relevance of family type to fertility desire among couples in Nigeria. The fertility desire of husbands in a polygynous marriage was about four children compared to fertility desire of one child of husbands in a monogamous marriage. The currently high and stalled fertility level in Nigeria necessitates new approaches to influence fertility desire. Family planning policy and intervention programmes should also target the polygynous family type, especially with focus on men within this family setting due to their high desire for more children. In addition, because of the roles of men as the heads of most families and major decision-makers in the Nigerian society, they should be integrated into such programmes. Predisposing factors of fertility desire for more children, such as the region, religion and contraceptive use of couples, should be addressed in activities towards affecting fertility desire for more children. In addition to awareness campaigns, encouraging couples to use contraceptives with consideration of their religious beliefs should be considered. Therefore, to achieve the Sustainable Development Goals one, three, four and five, existing intervention programmes and policies need evaluation and revision to take cognisance of factors associated with fertility desire for more children among couples.


We report (i) the relative abundance of the ssc-miR-1285, miR-16, miR-4332, miR-92a, miR-671-5p, miR-4334-5p, miR-425-5p, miR-191, miR-92b-5p and miR-15b miRNAs, and (ii) the presence of 347 up-regulated and 174 down-regulated RNA transcripts in high-fertility breeding boars, based on differences of farrowing rate (FS) and litter size (LS), relative to low-fertility boars in the  AI program. An overrepresentation analysis of the protein class (PANTHER) identified significant fold-increases for C-C chemokine binding (GO:0019957): CCR7, which activates B- and T-lymphocytes, 8-fold increase), XCR1 and CXCR4 , cytokine receptor activity (GO:0005126): IL23R receptor of the IL23 protein, associated to JAK2 and STAT3, 3.4-fold increase), the TGF-receptor (PC00035) genes ACVR1C and ACVR2B (12-fold increase). Moreover, two micro-RNAs (miR-221 and mir-621) were down- and up-regulated, respectively, in high-fertility males. In conclusion, boars with different fertility performance possess a wide variety of differentially expressed RNA present in spermatozoa that would be attractive targets as non-invasive molecular markers for predicting fertility. In the study presented here we identified transcriptomic markers for fertility in the cargo of pig ejaculated spermatozoa using porcine-specific micro-arrays (GeneChip Just minutes after natural mating or artificial insemination (AI) boar spermatozoa reach the sow oviduct , and incIn mammals, spermiogenesis implies crucial changes of cell differentiation in round spermatids that leads, among other specific modifications, to the loss of most of their cytoplasm before becoming a testicular spermatozoon that soon moves from the seminiferous epithelium towards the epididymis. Further maturational changes occur in the epididymis, including compaction of the nuclear genome , that leIn this relation, decreased levels of miR-10b, and miR-135b in asthenospermic human sperm samples compared to healthy controls  and otheThe same reasoning would also apply to markers based on gene expression, even when spermatozoa are supposed to be transcriptionally silent . In The present study aimed therefore to determine the relative load (in terms of expression levels) of miRNAs and mRNAs in ejaculated boar spermatozoa, including the relation of any differential RNA cargo with fertility characteristics post AI. Microarray-based technology was used to study either (i) relative abundance of miRNAs on boar spermatozoa and (ii) total RNA differential expression between high fertile and low fertile boars. The hypothesis tested was that the available RNA-cargo in ejaculated spermatozoa includes specific transcripts whose level of expression is enriched in high-fertility breeding boars and thus could be valuable biomarkers for fertility.n = 3), and then analyzed with the GeneChip™ miRNA 4.0 Array. Of the 326 pig (Sus scrofa)-specific miRNAs included in the array, 10 miRNAs had an expression of more than 10 average expression units , with these being miR-1285, miR-16, miR-4332, miR-92a, miR-671-5p, miR-4334-5p, miR-425-5p, miR-191, miR-92b-5p and miR-15b  identified up to 521 differentially expressed genes (DEGs), among which 374 were up-regulated in high-fertility (n = 4) as compared to low-fertility (n = 3) males  males . When we performed a more stringent analysis of these DEGs , 67 out In terms of molecular function C,D, bothp < 0.05) relative to the expected genes present in the genome of Sus scrofa.An over-representation analysis (PANTHER)  allowed Finally, the analysis of a plausible interconnection between target genes of those miRNAs detected in experiment 1  and the DEGs in the PORGENE-array in experiment 2 is presented in The microarray platform analysis used here and, in particular the multispecies miRNA array, have allowed us to define the relative abundance or cargo for large numbers of non-coding small RNAs present in spermatozoa retrieved from the SRF of boar ejaculates. An alternative would have been to use qPCR, but the latter is highly reliant on the number and selection of housekeeping genes . The micin vitro model for the induction of oxidative stress [URGCP (upregulator of cell proliferation) [FGFR2 [FGFR2 has been defined as non-essential for spermatogenesis and fertility in mice [E2F6, a key regulator of the cell cycle and apoptosis [IL-23 have been correlated [IL-23 play critical roles in the induction of Th17 differentiation and governs local inflammation [Only a few miRNAs out of the detected 326 pig-specific miRNAs were abundant. Of those in abundance, the miR-1285 has been related to sperm production, and considered inhibited by 17β-estradiol, the latter (estradiol) also promoting AMPK phosphorylation . Moreovee stress . This ise stress . The miRe stress  and alsoe stress . Both oferation)  and also in mice , it coul in mice . Its prepoptosis  and, togpoptosis . Thus, trrelated  and its ammation , so it mammation , potentiammation  as well ammation  and an iammation . Interesammation . Sus scrofa annotated genes and also of non-coding RNAs. The overall results showed differential gene expression with 347 up-regulated genes and 174 down-regulated genes in high-fertility boars relative to low-fertility boars. These findings are relevant based on the fact that the boars with different specific fertility included in the present study were breeding boars, highly selected for sperm quality, a pre-requisite for inclusion in programs of artificial insemination. All boars had normal semen quality, in terms of sperm numbers, sperm motility, sperm morphology and absence of inflammatory; contrasting with other species as human, or even other animal classes [Wnt2, BDNF and CREB-related genes [CREB3L2 (p<0.05) in the uterus and utero-tubal junction in the porcine female genital tract in response to both mating and artificial insemination. Finally, it is also related to PI3K-Akt and the estrogen signaling pathway [The main focus of the second experiment was to identify, via microarray analysis, which transcripts were differentially expressed in ejaculated spermatozoa from breeding boars, highly selected for fertility after artificial insemination in commercial programs. The boars selected had fertility data based on more than 100 artificial inseminations up to 540) per boar. The analyses of fertility resulted in two clear subgroups according to their deviation in farrowing rate (FR) and litter size (LS) from the average direct boar effect recorded by the boar population of the same genetic line: high-fertility boars (FR > 0.45 and a LS > 0.15); and low-fertility boars (FR < −0.12 and LS < −0.18). These fertility results show the true differences in the fertile potential of boars, since they were specifically recorded to show the direct effect of the boar on fertility, which was possible by using the statistical model developed by Broekhuijse et al. , and rep classes  that had classes , and it  classes . Thus, i0 per boaKCNA3 , KCNIP3 , KCNH4; LOC100620256 , LOC102159765 , KCTD9 (potassium channel tetramerization domain containing 9), CNGA4 . Among these channels, only KCNA3 has been characterized in rat testis as well as identified not only in the cytoplasm of primary spermatocytes and post-meiotic elongating spermatids, but also in the head and tails of epididymal spermatozoa [CATSPERG (catsper channel auxiliary subunit gamma) is up-regulated whereas the CATSPERB (catsper channel auxiliary subunit beta) was down-regulated in high-fertility boars. These two last transcripts are subunits of catsper, a channel involved in boar sperm motility during in vitro capacitation [CATSPERB and CATSPERG, the latter associated with CATSPER1 [CATSPER is linked to an increase on a reactive oxygen species (ROS) generation [Overall See , DEGs, wrmatozoa . Whethercitation . The CATCATSPER1  and the neration  and it ineration .LOC100739821 (zinc finger MIZ domain-containing protein 2), ZNRF4 (zinc and ring finger 4), LOC100512674 (zinc finger protein 367), LOC100511053; LOC100624021 (zinc finger protein PLAGL2), ZFAND3 , ZNF25 (zinc finger protein 25), ZDHHC7 , ZNF268 (zinc finger protein 268), ZNHIT6 , ZNF568 (zinc finger protein 568), LOC102163983 (zinc finger protein 341). Among these, ZDHHC7 is directly involved in signaling via membrane-localized estrogen receptors (ER) [ZNF568 in a later event, being expressed in 3-5 week old embryos and potentially is related to embryogenesis [ZNF283 (zinc finger protein 283), FEZF2; LOC100622205 , GLI1; LOC100621250 . Interestingly, down-regulation in high fertility males is in accordance with a previous study on GLI1 up-regulation in transgenic mice leading to a blockage of spermatogenesis in pachytene [Moreover, a representative number of transcripts included in the list of our DEGs were related to Zinc finger proteins (ZNF), one of the most abundant group of proteins with a wide variety of functions, including transcriptional regulation, ubiquitin-mediated protein degradation, signal transduction, actin targeting, DNA repair and cell migration . The majors (ER)  and the ors (ER) . We conjachytene . This geachytene .LOC100152461; LOC100627430; NFYA , TCF21 (transcription factor 21), LOC100524199; LOC100620736 (transcription factor 25), MBTPS2 , MTF2 , but some are also down-regulated in high-fertility boars: UBTFL1 .Transcription factors are also represented among our results of DEGs. Not only are they up-regulated in high-fertility boars: EGFR) [ADAM gene has been previously described by our group, mainly in terms of biological adhesion but also in terms of pH regulation of the utero tubal junction in sows [ADAM7  and ADAM29 . ADAM7 in mouse spermatozoa is required for normal fertility [LOC102162067 , IL23R (interleukin 23 receptor), IFN-DELTA-4; LOC100736862 , IFNK , LOC100736882 (interferon lambda receptor 1-like) and IFIT3 (interferon-induced protein with tetratricopeptide repeats 3), however similar genes were also found to be up-regulated in high-fertility boars: IRF3 (interferon regulatory factor 3) and ISG20L2 (interferon stimulated exonuclease gene 20kDa-like 2).The matrix metalloproteinases (ADAM) are involved in several processes such as cell adhesion and immune related signaling, including the activation of TNF-alfa and generation of the active forms of Epidermal Growth Factor Receptor (EGFR) . In fact in sows ,61. In tertility , and herertility . WhetherCDH10, CDSN, ITGB8, ANGPTL1, CTNNA3) were found only to be down-regulated in high-fertility boars. In contrast, genes related to signaling  and cellular component organization or biogenesis  were only identified as up-regulated in high-fertility boars. Cadherin-10 (CDH10), the type II classical cadherin, a protein binding molecule in terms of molecular function and is used as a biomarker in the prognosis of certain types of cancer [CDSN is involved in skin immune-related disease [ITGB8 is involved in the endometrial receptivity through VAV-RAC1 signaling axis via FAK to facilitate the endometrial epithelial cell receptivity for the attachment of blastocyst [ANGPTL1, Angiopoietin-like proteins is involved in several processes from lipid and glucose metabolism to inflammation [CTNNA3 , whose gene dosage compensation of CTNNA3 and p57KIP2 in the placenta shares a conserved regulatory mechanism that correlates with an early step in trophoblast determination [CCNJ), down-regulated in high-fertile boars, is involved in cell cycle regulation, but without any apparent described function in spermatogenesis or fertility performance. Regarding up-regulated genes in high-fertility boars, ZRI1 permits DNA damage-induced apoptosis of cells in the germline by an unknown cell non-autonomous mechanism [ZNHIT6 is required for the maintenance of correct protein folding under heat stress conditions [In order to categorize the overall DEGs resulted from our study, we performed a biological function analysis (PHANTER) of the DEGs which resulted in a differential function depending on the fertility performance of the boars. Thus, biological adhesion-related genes , a translational regulator involved in long-term memory storage maintenance in synaptic connections in neurons [CXCL16 appears to be an initiator for the molecular crosstalk that enhances decidualization of the endometrial stromal cells [If we categorize according to molecular function, one of the main findings was the cytoplasmic polyadenylation element-binding protein 3 , which acts through the CCR7 receptor to regulate Treg cell recruitment and retention in peripheral tissues [CCR7 receptor in high-fertile boars. In addition, CXCR4, is the main G-coupled receptor of CXCL12, involved in several diseases in the female reproductive tract, mainly through inflammatory processes [A further analysis of the overrepresentation analysis in terms of molecular function reveals an important component on chemokine binding (GO:0019957). Regulatory T (Treg) cells facilitate maternal immune tolerance of the hemi-allogeneic conceptus in early pregnancy. In this regard, seminal fluid induced expression of mRNA encoding the Treg chemokine  tissues . Our resrocesses . In agreACVR1C and ACVR2B were down-regulated in high-fertility males. Activin affects many aspects of cellular development, including those essential for reproductive fitness and, in fact, activin receptor transcript levels also change, with Acvr1 (encoding ALK2) and Acvr2b (ActRIIB) significantly higher and lower, respectively in the proliferation of mouse testis [We have also observed in our analysis of protein class overrepresentation, that the e testis .UBQLNL, CPEB3, DESI1 and ATG9A) and down-regulation in high- relative with low-fertile boars were found both link to miR-16 and miR15b. In common with miR-92b we identified the transcript CPEB3, and the specific genes related solely to this miRNA: TCF21, PDZD8. Finally, in relation with miR-16, the gene BAG4 appeared up-regulated in the DEGs analysis performed with microarrays. The UBQLNL is a testis-specific gene, not indispensable due to a compensatory mechanism in mice, but involved in the elongation of spermatids and found up-regulated in high-fertile boar samples [SAE1), essential for the maintenance of hematopoietic stem/progenitor cell in zebrafish [DESI1 (desumoylating isopeptidase 1), a second class od SUMO-related proteases [ATG9A (autophagy related 9A) is essential for autophagy, being trafficked to sites of autophagosome formation [LRRN3 gene in high-fertility boars, with LRRN3 being involved in Ras-MAPK signaling by facilitating internalization of EGF in clathrin-coated vesicles [TCF21 (transcription factor 21) is a key inactivation factor of the PI3K/AKT signaling pathway and also of matrix metalloproteinases [PDZD8 being up-regulated in high-fertility boars. BAG4 (BCL2-associated athanogene 4) was found to be up-regulated in high-fertility boars, forms a complex with annexin 7 and is positively correlated with levels of Hsp70 and Bcl-2, these two last inhibiting the Cytochrome C dependent activation of Caspase-3, and also involved in mitochondrial apoptosis [Finally, in an attempt to address a prospective functional approach to the high-expressed miRNAs, we contrasted the target genes of the most abundant miRNA (with a target match of more than 0.9. miRbase and miRDB ), and fo samples . It is a samples . In relaebrafish  and alsoroteases . The genormation . Finallyvesicles . TCF21  and current Swedish legislation (SJVFS 2017:40). All procedures were performed according to the European Directive 2010/63/EU, 22/09/2010 for animal experiments and current Swedish legislation (SJVFS 2017:40. Date: 06/2016) and approved by the Bioethics Committee of Murcia University (research code: 639/2012) and the “Regional Committee for Ethical Approval of Animal Experiments” (Linköpings Djurförsöksetiska nämnd) in Linköping, Sweden (permits no. 75-12 and no. ID1400. Date: (12/2017)).The chemicals used in the experiments were of analytical grade. Unless otherwise stated, all reagents were acquired from Sigma-Aldrich .n = 3) of proven sperm quality  of Swedish Landrace breed were recruited from a controlled breeding farm. The animals were individually kept in separate pens at the Translational Medicine Centre (TMC/CBR-3) of Linköping University under controlled temperature and light regimes (12 h:12 h light/dark cycle). For experiment 2, healthy, mature (1–2 years old) boars of Landrace and Large White breeds with proven fertility were housed in a commercial artificial insemination (AI) enterprise . All boars were fed with commercial feedstuff well-adjusted to nutritional requirements of adult AI boars, provided with water ad libitum and receiving the same management. Throughout all experiments, animals were handled carefully and in such a way as to avoid any unnecessary stress. The sperm-rich fraction (SRF) was collected using the gloved-hand method yielding, in experiment 1 a total of thirty ejaculates (ten ejaculates per boar) and, in experiment 2, 28 ejaculates from 7 different boars (one ejaculate/boar/month). All ejaculates used in the experiments fulfilled the standards of quantity and sperm quality requirements for AI-doses . In all cases, spermatozoa were separated from seminal plasma immediately after ejaculate collection by double centrifugation  and the resulting sperm pellets were stored at −80°C .For experiment 1, young mature boars  were used for analyze the miRNA expression profile, after RNA isolation.Each collected SRF was evaluated for sperm concentration and motility (velocity and forward progressive motility) using a light microscope  equipped with a thermal plate (38 °C), positive phase contrast optics (10× objective), a Charge Coupled Device (CCD) camera , and the Qualisperm® Software . Ejaculates with at least 70% motile and 75% morphologically normal-looking spermatozoa immediately after collection were used for the experiments. Ten boar ejaculates (SRF) from each male (n = 28) used in the experiment were collected over a period of four months (one ejaculation per boar and month), while in the same period two other ejaculates were collected per week from the same boars and used to inseminate a total of 1722 sows, whose fertility data in terms of farrowing rate and litter size were recorded. The raw fertility data were statistically corrected for parameters related to farm and sow in order to isolate the contribution of the individual boars . The din = 4) or low (n = 3) fertility based in more than 100 artificial inseminations (up to 540) per boar, according to their farrowing rate (FR) and litter size (LS): high-fertility boars with a FR > 0.45 and a LS > 0.15; and low-fertility boars with FR < −0.12 and LS < −0.18. Four ejaculates from each boar were used for analyzing the differential gene expression profile, after RNA isolation.Thus, the 7 boars were classified as having high  and the upper aqueous phase (400 μL) was transferred into a gDNA eliminator column (Quiagen), to avoid DNA contamination in the purified RNA. After centrifugation , the resulting phase, free of genomic DNA, were mixed with 600 μL of 100% ethanol by gentle pipetting. A total of 700 μL of sample were transferred into a RNeasy MinElute spin column  in a 2 mL collection tube and centrifuged  in order to allow that RNA bound to the membrane. The flow-through was removed and this step was repeated with the rest of the sample (300 μL) using the same column. Later, the column was sequentially washed with 700 μL of RWT buffer , 500 μL of RPE buffer  and 500 μL of 80% ethanol , discarding the flow-through in each washing. Finally, the column was dried  and the flow-through was discarded. RNA was eluted by placing 14 μL nuclease-free water in the spin column membrane and centrifuging . Total RNA content and its quality was determined by NanoDrop® 1000 . Only samples with high RNA quality were snap-frozen in liquid nitrogen and stored at −80 °C for its further analysis. For both experiments, the RNA was obtained using a commercially available kit designed to isolate cell-free RNAs for low quantity samples , following the manufacturer protocol. In brief, each sample (200 μL) was thawed on ice, homogenized and RNA was extracted using 200 μL of QIAzol Lysis Reagent . Samples were mixed by pipetting and incubated  followed by addition of 200 μL of chloroform. The mixture was shaken vigorously  and incubated . Phases were separated by centrifugation , following the manufacturer guidelines. Biotin-labeled RNA was synthesized using Affymetrix® FlashTagTM Biotin HSR RNA Labelling Kit . Briefly, 100 ng of total RNA were subjected to poly-A tail incorporation to 3′-end and, subsequently, a biotin-labeled 3DNA molecule was joined to the 3′-end using DNA ligase. MiRNA expression profiling was carried out using Affymetrix® Whole Transcript Plus reagent kit  following the manufacturer protocol [Total RNA (75 ng) from each sample were used to make cDNA using GeneChipprotocol .® Fluidics Station 450 , to be finally scanned using the Affymetrix GeneChip® scanner GCS3000 .Finally, 21.5 μL of biotin-labeled sample (experiment 1: miRNA arrays) or 41 μL of fragmented and labelled single stranded cDNA (experiment 2: microarrays) were mixed with 110.5 μL or 109 μL, respectively, of hybridization master mix to make a cocktail hybridization mix for a single reaction. The hybridization cocktail was then incubated first at 99 °C for 5 min, followed by a descent to 45 °C until loaded on the array chip . A total of 130 μL of the cocktail hybridization mix was loaded into each array chip and was incubated at 45 °C under 60 rotations per min, for 18 h (16 h for the microarrays in experiment 2). The hybridized cartridge array chip was then unloaded and subjected to washing and staining using a GeneChip2 transformation for extracting the expression values of each transcript in the probe set, as implemented in the official Transcriptome Analysis Console  from Affymetrix. Molecular and biological functions as well as of overrepresentation analysis were identified using PANTHER GO [The intensity data of each array chip was processed using the robust multi-array average (RMA) normalization, computing average intensity values by background adjustment, quantile normalization among arrays and finally logNTHER GO .® Transcriptome Analysis Console software . Experiment 1: a pool of 10 ejaculates for each male (n = 3) were used for miRNA analysis. The average expression in the arrays (Mean ± Standard Deviation of the log2 average expression) were used for describing the differential expression intensities analyzed by the miRNAs array. Experiment 2: one comparation were performed between the high  and low  fertility boars. The differential expressed genes (DEGs) that fulfilled the criteria  were extracted as significantly up- or down-regulated transcripts. Finally, the analysis of the target genes, with a score of more than 0.9. in the miRDB [Statistical analysis was performed by Affymetrixhe miRDB  was usedAn overrepresentation analysis of the protein class (PANTHER) identified significant fold-increases for C-C chemokine binding (GO:0019957): CCR7 which activates B- and T-lymphocytes, 8-fold increase), XCR1 and CXCR4 , cytokine receptor activity (GO:0005126): IL23R receptor of the IL23 protein, associated to the JAK2 and STAT3, 3.4-fold increase), the TGF-receptor (PC00035) genes ACVR1C and ACVR2B (12-fold increase). Moreover, two micro-RNAs (miR-221 and mir-621) were down- and up-regulated, respectively, in high-fertile males. In conclusion, boars with different fertility performance depict a differential RNA cargo that would be an attractive battery of non-invasive molecular markers predicting fertility.


There have been few systematic studies regarding clearance of uric acid (UA) in patients undergoing peritoneal dialysis (PD). This study investigated peritoneal UA removal and its influencing factors in patients undergoing PD.This cross-sectional study enrolled patients who underwent peritoneal equilibration test and assessment of Kt/V from April 1, 2018 to August 31, 2019. Demographic data and clinical and laboratory parameters were collected, including UA levels in dialysate, blood, and urine.2; P = 0.008). Furthermore, higher transporters (high or high-average) exhibited greater peritoneal UA clearance, compared with lower transporters (low or low-average) . Among widely used solute removal indicators, peritoneal creatinine clearance showed the best performance for prediction of higher peritoneal UA clearance in receiver operating characteristic curve analysis , 0.93–0.99]. Peritoneal UA clearance was independently associated with continuous SUA  and hyperuricemia  status, only in patients with lower (≤2.74 mL/min/1.73 m2) measured glomerular filtration rate (mGFR). In those patients with lower mGFR, lower albumin level , lower body mass index , higher transporter status  and greater dialysis dose  were independently associated with continuous peritoneal UA clearance. Furthermore, each 1 kg/m2 decrease in body mass index , each 1 g/dL decrease in albumin level , and each 0.1% increase in average glucose concentration in dialysate  were associated with greater peritoneal UA clearance (> 39.8 L/week/1.73m2).In total, 180 prevalent patients undergoing PD (52.8% men) were included. Compared with the normal serum UA (SUA) group, the hyperuricemia group showed significantly lower peritoneal UA clearance (39.1 ± 6.2 vs. 42.0 ± 8.0 L/week/1.73mFor patients undergoing PD who exhibited worse residual kidney function, peritoneal clearance dominated in SUA balance. Increasing dialysis dose or average glucose concentration may aid in controlling hyperuricemia in lower transporters. Uric acid , as the end-products of endogenous and dietary purine metabolism, is a weak diprotic acid that possesses two dissociable protons with a pKa1 of 5.4 and pKa2 of 10.3, respectively [Peritoneal dialysis (PD), a widely used dialysis modality, is becoming increasingly important in renal replacement therapy for patients with end-stage renal disease for its cost-effectiveness and related improvements in techniques and patient survival . The preThis single-center cross-sectional study enrolled patients who had undergone peritoneal equilibration test (PET) and assessment of Kt/V in our PD center from April 1, 2018 to August 31, 2019. The inclusion criteria included prevalent patients aged ≥18 years who had initiated PD therapy at least 1 month prior to PET and Kt/V tests. Patients were excluded if they had taken UA-lowering agents within 1 month before PET and Kt/V tests, had transferred from long-term hemodialysis , had undergone failed renal transplantation, or exhibited malignant tumors. All enrolled patients used standard lactate-glucose peritoneal dialysate . Relevant clinical parameters were tested in the clinical laboratory of the First Affiliated Hospital of Sun Yat-sen University using standard methods. All patients provided written informed consent to participate. The study was performed in accordance with the ethical principles of the Declaration of Helsinki and was approved by the Clinical Research Ethics Committee of the First Affiliated Hospital of Sun Yat-sen University.Demographic data were collected, included age, sex, body mass index (BMI), diabetes status, cardiovascular disease status, and primary kidney disease. Data of the first PET and Kt/V tests during the study period were collected. The PD-related data that were collected included dialysis vintage, dialysis dose, average glucose concentration in dialysate, measured glomerular filtration rate (mGFR), Kt/V, weekly total creatinine clearance (CCL), 24 h residual urine volume, normalized protein catabolic rate and standard PET data. The standard PET data described the urea, creatinine, and UA levels in dialysate, blood, and urine samples with 2 L of 2.5% dextrose dialysate dwelling for 0, 2 or 4 h; 0 h was the time point in the PET test when all of the 2 L dialysate flowed into abdominal cavity, and the duration of this process was recorded. Patients undergoing PD were classified into high, high average, low average, or low transporters, in accordance with Twardowski’s criterion . Clinica2) and higher (> 2.74 mL/min/1.73m2) mGFR group, respectively. Following exclusion of the potential effects of multicollinearity, variables that were significant in univariate analysis (P < 0.05) and those that exhibited clinical correlations were entered into the final model. The performances of small solute removal indicators for prediction of higher peritoneal UA clearance were tested using area under the receiver operating characteristic curve analysis. Two-sided P values < 0.05 were regarded as statistically significant. All statistical analyses were conducted in SPSS Statistics software .Enrolled patients were divided into two groups according to median peritoneal UA clearance. Data are presented as mean ± standard deviation for normally distributed continuous variables, medians (interquartile range) for non-normally distributed continuous variables, and frequencies and percentages for categorical variables. Differences between the lower and higher peritoneal UA clearance groups were analyzed using independent samples t-tests for normally distributed continuous variables, the Mann–Whitney U test for non-normally distributed continuous variables, and chi-squared tests for categorical variables. Pearson correlation or Spearman rank correlation test were used to evaluate correlations between variables of normal or skewed distribution, respectively. Multiple linear regression and binary logistic regression were performed to explore the independent influencing factors of continuous and categorical SUA and peritoneal UA clearance in total, lower . As shown in Fig. r = 0.97; P < 0.001). Moreover, correlations were similar between 4 h D/P UA and peritoneal UA clearance  and between 4 h D/P creatinine and peritoneal UA clearance  , peritoneal UA clearance was negatively correlated with SUA  . The further analysis of multiple linear regression and binary logistic regression shown in Table P = 0.01) and hyperuricemia status , only in patients undergoing PD who had lower mGFR.The distribution of SUA in patients undergoing PD is shown in Fig. 01) Fig. c and d. P = 0.01) and BMI  were both negatively associated with peritoneal UA clearance, while the higher transporter status  and dialysis dose  were positively associated with peritoneal UA clearance in the lower mGFR group. Similarly, binary logistic regression analysis revealed that each 0.1% increase in average glucose concentration in dialysate , each 1 g/dL decrease in albumin level , and each 1 kg/m2 decrease in BMI  were independently associated with greater peritoneal UA clearance (> 39.8 L/week/1.73m2)  is near that of creatinine (113 Da); in addition, few circulating UA molecules are bound to albumin or affected by electrochemical gradient, whereas serum phosphorus molecules are affected in this manner . The preA negative correlation was observed between peritoneal UA clearance and SUA in the present study; further multiple linear and logistic regression analyses suggested that greater peritoneal UA clearance was significantly associated with lower SUA only in patients undergoing PD who had relatively low mGFR. This suggests that the kidney still plays an indispensable role in removing excessive SUA in patients with residual kidney function; and the importance of peritoneal UA clearance gradually became evident with the decline of residual kidney removal. Therefore, the high SUA in patients undergoing PD who had unsatisfying renal function may have been partially caused by inadequate UA removal during PD. In the present study, we found that lower BMI and albumin level, higher transporter status, greater dialysis dose, and higher glucose concentration in dialysate were significantly associated with greater peritoneal UA clearance in the lower mGFR group. BMI is a body composition parameter, which was strongly correlated with BSA in this study (data not shown); accordingly, patients undergoing PD who had lower BMI may exhibit greater peritoneal UA removal, after adjustment for their relatively lower BSA. In addition, the serum albumin level was revealed to be associated with both continuous peritoneal UA clearance and higher peritoneal UA clearance category in patients with worse renal function. Previous studies have shown negative correlations between peritoneal albumin loss and serum albumin level in patients undergoing PD , 28. FurP = 0.052); however, the effect was shown to be statistically significant in logistic regression . Therefore, the positive effect of the glucose concentration in dialysate may have been masked by the relatively small sample size after grouping based on residual kidney function.Notably, few studies have explored PD-related factors associated with greater peritoneal UA clearance, particularly in terms of residual kidney function; average UA clearance in PD was revealed to be positively proportional to the exchange volume and flow rate . In the There were some limitations in our study. First, the cross-sectional observational study itself only assessed associations rather than causal relationships. Second, this study did not explore the effects of different PD modalities  or different exchange flow rate on peritoneal UA clearance. Third, the dialysis vintages of enrolled patients were relatively short, which may have led to bias involving inadequate and unstable dialysis. Fourth, this study used a small sample size of patients without residual kidney function; therefore, classification of residual kidney function was grouped on the basis of median mGFR, rather than the clinical standards of oliguria or anuria. Despite the above limitations, to the best of our knowledge, this was the first study to systematically explore the contributions of peritoneal UA clearance and residual kidney removal, and to identify independent factors that influence peritoneal UA clearance. In this study, we concurrently collected common small solute removal indicators for further comparison and analysis, which provides important guidance in optimizing prescription for achievement of better SUA control in patients undergoing PD, especially those with worse residual kidney function. Moreover, we excluded patients undergoing PD who had a history of taking UA-lowering agents, which enabled us to more specifically study UA clearance in PD regimen.In summary, UA removal in patients undergoing PD was found to be more rely on peritoneal clearance, especially in patients with relatively worse residual kidney function. Peritoneal CCL may be an optimal indicator for assessment of UA removal during PD because of its similar removal characteristics through the dialysis membrane. For patients with unsatisfactory residual kidney function, increasing the dialysis dose or average glucose concentration in dialysate may aid in controlling hyperuricemia, particularly in patients who are lower transporters.


Calcium signaling and the AMP-activated protein kinase (AMPK) signaling networks broadly regulate numerous aspects of cell biology. Human Cytomegalovirus (HCMV) infection has been found to actively manipulate the calcium-AMPK signaling axis to support infection. Many HCMV genes have been linked to modulating calcium signaling, and HCMV infection has been found to be reliant on calcium signaling and AMPK activation. Here, we focus on the cell biology of calcium and AMPK signaling and what is currently known about how HCMV modulates these pathways to support HCMV infection and potentially contribute to oncomodulation. Human Cytomegalovirus (HCMV) infection is a prevalent opportunistic pathogen, infecting ~60–90% of the global population Pass, . It remaHCMV can spread through mucosal membranes, via blood, through the placenta and breast milk from mother to child, or through saliva and sexual secretions. Primary infection and viral replication occur in a wide variety of cell types including fibroblasts, epithelial cells, endothelial cells, mononuclear cells, and neural progenitor cells  dependent protein kinase kinase (CaMKK) is encoded by two genes, CAMKK1 and CAMKK2 resulting in the expression of CaMKKα (or CaMKK1) and CaMKKβ (or CaMKK2) proteins, originally studied in rat brain , within the CaM binding domain of CaMKK, will block CaM from binding thus inhibiting CaMKK activity . All contain similar autoinhibitory domains, which require release via phosphorylation by CaMKK and Ca2+-CaM binding for full activation . Each varies slightly in size and contains a variable linker region which can produce splicing isoforms. The isoforms are differentially expressed in multiple tissues throughout the human body  and serum response element (SRE). CaMKII further facilitates transcriptional changes, often associated with osteoblast differentiation, thus stimulating bone mineralization , solely requires CaM-binding for its activation  which acts as an agonist for human chemokines (CXCR1 and CXCR2) responsible for intracellular calcium release. This chemokine response also has implications in neutrophil recruitment, which then act as passive carriers of the virus. These data suggest that calcium signaling plays a role in viral dissemination through the host  is often amplified, while mutations in the PRKAA2 gene occur less frequently (Monteverde et al., There are reports indicating mutational changes of the AMPK subunits in cancer. First, some evidence suggests that AMPKα1 acts as an oncogene, while α2 may act as a tumor suppressor. The AMPK activator, LKB1, is encoded by the gene Many canonical AMPK activities lend themselves to AMPK acting as a tumor suppressor, and therefore loss of expression would promote tumorigenesis (Shackelford and Shaw, As evidenced above, both calcium and AMPK play central roles in the cellular stress response and intersect with each other in the cytosol . CalciumCellular stress often affects cell proliferation, apoptosis, cell cycle, and the immune response, so it is not unreasonable to think that, in some way, each pathway contributes to modulating host cell homeostasis and HCMV infection. HCMV has adapted to carefully control calcium signaling through many of its gene products, US28, US21, UL37, and UL146, as well as through the manipulation of calcium signaling protein, CaMKK. HCMV also acts downstream of CaMKK, on AMPK, to further manipulate host cell transcription and more specifically, host cell metabolism for the benefit of the virus. There is significant overlap in the downstream consequences of calcium and AMPK signaling, yet the downstream functional targets of these pathways that control HCMV infection are largely unknown. Identifying them and elucidating their contributions to infection will greatly increase our understanding of how these host pathways contribute to infection and could potentially identify targets for therapeutic intervention.Studies focusing strictly on calcium signaling in the brain and AMPK activity in cardiac or skeletal tissues have opened the door to many unanswered questions about how these signaling pathways contribute to cellular function and various pathologies in other tissues. Many of the proteins discussed above are ubiquitously expressed in all cell types and perform basal functions in normal cells. HCMV infection occurs in a broad range of host cells, and both calcium and AMPK signaling play a significant role during infection. One major question that remains largely unanswered, is how do these signaling pathways contribute to latent HCMV infection? It has been suggested that a lack of calcium signaling, for instance, in the brain may contribute to low lytic infection and inadvertently promote latency in these cells (Miller et al., Lastly, HCMV infection has been associated with numerous types of cancers as discussed above. Many cancers rely on AMPK and calcium signals to promote tumor formation and survival. Although many of these associations are not fully understood, there is evidence that HCMV infection promotes oncomodulation, and this could be mediated by viral modulation of calcium and AMPK signaling. For example, the prevalence of the HCMV gene US28, which is responsible for intracellular calcium mobility (Gao and Murphy, DD wrote the manuscript and created the figures. DD and JM contributed to the content and editing of this manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We use individual-level census data for England and Wales for the period 1851–1911 to investigate the interplay between social class and geographical context determining patterns of childbearing during the fertility transition. We also consider the effect of spatial mobility or lifetime migration on individual fertility behavior in the early phases of demographic modernization. Prior research on the fertility transition in England and Wales has demonstrated substantial variation in fertility levels and declines by different social groups; however, these findings were generally reported at a broad geographical level, disguising local variation and complicated by residential segregation along social class and occupational lines. Our findings confirm a clear pattern of widening social class differences in recent net fertility, providing strong support for the argument that belonging to a certain social group was an important determinant of early adoption of new reproductive behavior in marriage in England and Wales. However, a relatively constant effect of lower net fertility among long-distance migrants both before the transition and in the early phases of declining fertility indicates that life course migration patterns were most likely factor in explaining the differences in fertility operating through postponement of marriage and childbearing.The online version contains supplementary material available at 10.1007/s13524-020-00895-3. The vast body of research on the determinants of the historical fertility transition has generally located its origins at the time, in the late nineteenth and early twentieth century, when contemporaries first started noticing profound changes in fertility in their society. A century or more later, we have a far more complete understanding of the timing of the process and overall patterns of decline, but the precise causal pathways that led to reduced fertility remain somewhat speculative and subject to debate Becker . A partiBroadly defined, explanations of fertility decline often distinguish between two concepts of behavioral change—innovation and adjustment—that need to occur before new reproductive habits are adopted Carlsson . The innAdherents to the two forms of explanation generally agree that analysis of the extent of socioeconomic variations in fertility and how these are transformed during the process of fertility decline is fundamental to any understanding of the nature of fertility transition. Previous research has highlighted that socioeconomic differences in fertility tend to widen as fertility transitions begin and that the upper and middle classes were most often the first to move toward lower fertility  to investigate the effects of social class and spatial mobility on individual fertility behavior. The countries’ early industrialization and urbanization, geographically clustered industries, and complex occupational structure all provide an ideal setting in which to test the influence of class and increasing population mobility on fertility decline. Figure 851–1911 Research on the fertility transition in the British Isles has established that a substantial fall in marital fertility took place over the second half of the nineteenth century , provided via the Integrated Census Microdata (I-CeM) project . We consider only children under age 5 because in the nineteenth century living away from parents increased after that age. Nevertheless, a small percentage of children aged 0–4  were not living with their parents, most likely because of orphanhood or illegitimacy, or because they were staying with relatives or friends during the census enumeration. Thus We calculate recent marital net fertility for each married woman aged 15–54 in each census, whose spouse was present in the same household.Report on the 1911 census enquiry into the Fertility of Marriage  or registration districts (RD ≈ 600 units) as the main units of analysis Glass , 2000. RSC) and distance from place of birth or lifetime migration (LTM). We also include a number of individual-level control variables (Xt) in the model: age of woman, age difference between spouses, and husband’s household position (whether he was head of household):i refers to a woman, j refers to her RSD of residence, and γj is the RSD unit fixed effect.9Our analytical strategy takes two approaches. First, we measure the relationship between marital net fertility and individual-level characteristics and investigate how it changed during the first few decades of the fertility transition. We estimate the same set of models for all available census years: 1851, 1861, 1881, 1891, 1901, and 1911. The analysis follows a fixed-effects modelling strategy where marital net fertility is the dependent variable, and the two main variables of interest are social class (Table We note change in the distance that women migrated between birth and enumeration in the census. The percentage of women residing less than 10 km from their place of birth declined from 53% in 1851 to 49% in 1911. The main increase was in the category of long-distance migration (50+ km), which rose from 16% of women in 1851 to 24% in 1911. Thus, the absolute number of married women who had migrated 50+ km from their place of birth to their place of residence was more than three times higher in 1911 than in 1851.Increases in age at marriage and reductions in adult male mortality mean that in the later censuses, our population of currently married women aged 15–54 included a larger proportion of older women: the percentage of 20- to 24-year-olds declined from approximately 10.5% in 1881 to only 6.7% in 1911. The age difference between spouses decreased over time; the percentage of women married to a man of similar age (husband 0–2 years older) increased from 32% in 1851 to 38% in 1911. This was at the expense of large age gaps (of more than six years) between spouses, probably because declining mortality meant that there were fewer couples composed of a widower and his younger second wife.child-woman ratio (CWR) . The difference between the main model and M1 is that the latter uses only recently married women, whereas the main model uses women of all marital durations. We would expect recently married women to have higher fertility in the last five years for two main reasons. First, they are younger and more fecund, which is controlled for by the inclusion of age in the models. Second, the interval from marriage to first birth tends to be smaller than the intervals between births because there is no postpartum or lactational infecundability, and this is the reason for the differences between the main model and M1 estimates in Fig. The first model (M1) uses net achieved fertility as the dependent variable, using only the number of children alive at the time of the 1911 census born to those women aged 15–54 who had been married for less than five years. The second model (M2) uses another measure of fertility for the same population of women: the total number of children ever born, which also includes the children a woman might have lost prior to the census enumeration. Figure Differences between M1 and M2 in Fig. The net lifetime migration variable in Fig. 14We also tested whether a couple’s fertility behavior might have been independently influenced by the husband’s lifetime migration. The results of these models are presented in Fig. To explore whether the differences in net fertility were more responsive to the length of lifetime migration among some social classes than among others, we estimated a separate set of models for each social class in every census year. The national pattern in the fertility-migration relationship is largely guided by differences in the first five social classes; they demonstrate the same gradient across all census years. The exceptions are the three industrial classes , who also exhibited the shortest mean net lifetime migration distances across all census years  exhibited increasingly lower fertility than those born farther away, and this pattern emerged at the onset of fertility decline. Using 1881 census data, Day  suggestedirect diffusion—the working classes copying the family limitation practices used by higher social classes—hardly seems convincing in this context. This is particularly the case when the motivations driving childbearing and child-rearing practices, which were shaped by local and class-specific experiences, were also dramatically changing over the second half of the nineteenth century


Our findings show that the modification of an original melody in a real music changes the brain connectivity.In real music, the original melody may appear intact, with little elaboration only, or significantly modified. Since a melody is most easily perceived in music, hearing significantly modified melody may change a brain connectivity. Mozart KV 265 is comprised of a theme with an original melody of “Twinkle Twinkle Little Star” and its significant variations. We studied whether effective connectivity changes with significantly modified melody, between bilateral inferior frontal gyri (IFGs) and Heschl’s gyri (HGs) using magnetoencephalography (MEG). Among the 12 connectivities, the connectivity from the left IFG to the right HG was consistently increased with significantly modified melody compared to the original melody in 2 separate sets of the same rhythmic pattern with different melody ( It would be interesting to see how the brain reacts to phrases that contain prominent information such as a well-known melody while listening to real music, or phrases that do not. If this is something that can be detected without specific musical expertise, it would be interesting to see how the non-expert brain will react.Melody is a feature effortlessly extracted from music, which sometimes represents the music itself. Beethoven symphony No. 9 is known as “Ode to joy”, since the melody of “Ode to joy” appears repeatedly across the 4Theme is modified or repeated in 12 variations. Five conditions of the Theme, Variation I, Variation II, Variation III, and Variation IV are composed in the same key, harmony, meter, timbre, and ternary form. Among the five conditions, the original melody is present in the Variation II and IV. However, the original melody is significantly modified in the Variation I and III. In terms of rhythmic pattern, the Variation I and II are of 16th notes, while the Variation III and IV are of 8th notes. Hence, two sets of “Variation I vs. II” and “Variation III vs. IV” are of the same rhythmic patterns, but of different melodies  and the latter variations with modified melody (VMM). The original melody of “Twinkle Twinkle Little Star” in the melodies .The human brain has several interconnected key regions processing music, including bilateral inferior frontal gyri (IFGs) and Heschl’s gyri (HGs) –8. Each Effective connectivity for 12 connections between the bilateral IFGs and HGs was calculated by linearized time delayed mutual information (LTDMI) . LTDMI iVariation I vs. II” and “Variation III vs. IV”, with the original melody and modified melody, would consistently change effective connectivity between the bilateral IFGs and HGs.Therefore, we hypothesized that directional information transmission between related regions associated with the processing of intrinsic differences implied in the VOM and VMM would be reflected in the LTDMI between the bilateral IFGs and HGs. We further hypothesized that the two sets of “The study was approved by the Institutional Review Board of the Clinical Research Institute, Seoul National University Hospital (IRB No. C-1003-015-311). All experiments were conducted in accordance with the ethical guidelines and regulations.Twenty-five participants  were all right-handed . All participants had normal hearing, and had not received any formal musical training. Prior to the experiments, all the participants provided the informed consent in a written form.Theme, Variation I, II, III, and IV in Out of the theme and the 12 Variations in Mozart’s Variation on “Ah! vous dirai-je Maman” KV 265, we selected the five conditions of Theme, the number of 16th notes or 8th notes (in triplets) subdivided in accompaniments was the same between the Variation I, II, III, and IV.The time window was selected based on the concept of the motif . The ascThe present musical stimuli were recorded music, so those were presented without a break between movements of a theme and variations. To select the proper time window, we had to consider all the subdivided notes included in a quarter note in each time window in all conditions. The time window of 2,100 ms was the most suitable duration because (1) 2,100 ms covered the onset of the first quarter note to the offset of the last quarter note in the time window; (2) the number of additional notes did not exceed a quarter note in all the conditions; and (3) fade-out times of the final note in the preceding condition did not overlap with the onset of the time window in the following condition. The same phrases of the time window were repeated four times in each condition. However, to rule out the effect of repetition , we anal™, Helsinki, Finland). Electrooculograms (EOG) and electrocardiograms (ECG) were also simultaneously recorded to remove ocular and cardiac noise at a later time. We eliminated the environmental magnetic noise of raw MEG signals with the temporal signal space separation (tSSS) algorithm in MaxFilter 2.1.13  [The MEG signal was recorded with a sampling frequency of 1,000 Hz using a 0.1–200 Hz band pass filter in a magnetically shielded room with a 306-channel whole-head MEG System (Elekta Neuromag Vector ViewFinland) .™  at 100 dB. Visual stimuli of a silent movie clip  were presented on a screen to keep the participants awake [During the MEG recording, for about five minutes, all participants sat in a magnetically shielded room and passively listened to music . Musical stimuli were presented binaurally through plastic tubal silicone earpieces, 50 cm in length using STIM2ts awake , 23 whilz in Talairach coordinates (millimeters) were -53.5, -30.5, and 12.6 in the left HG, 55.4, -30.5, and 12.6 in the right HG, -55.5, 11.7, and 20.6 in the left IFG, and 53.5, 12.7and 20.6 in the right IFG, respectively (http://nitrc.org/projects/bnv/). The signal for each regional source of 4 ROIs  was extracted using a 14–30 Hz band-pass filter for each participant using BESA 5.1.8.10 , which was averaged at MATLAB 7.7.0.471 . Beta band rhythm of 14–30 Hz underlies the top-down control [The source coordinates for the ROIs of the bilateral HGs and IFGs were based on the standard Talairach coordinates; Heschl’s gyrus  and the inferior frontal gyrus ; the x, y, and ectively . In Fig  control , reflect control , and is  control  and cate control . ConsideFor the twelve connections among the bilateral HGs and IFGs, effective connectivity for twelve connections was estimated using LTDMI . The MI A(n) = B(n), the MI is maximum. When two time series are independent, the MI is zero. The directional information transmission between the two time series estimated based on TDMI, time delayed mutual information [In case of ormation :TDMIAB=TDMI is asymmetric MI obtained by adding a time delay. Both of linear and non-linear correlation between two time series can be detected by TDMI. The data length of 400 ms epoch in our study was insufficient in reconstruction of a reliable PDF for general TDMI.ρn)B(n+τ)A( or ρn)A(n+τ)B.The mean LTDMI value for the time window of 2,100 ms in each condition was calculated for the twelve connections between the four ROIs. Because the data set was not normally distributed, the differences in LTDMI values of the conditions including “Twinkle Twinkle Little Star” melody or not were tested by the Wilcoxon signed rank test using SPSS 21.0 software . Multiple comparisons for the twelve connections in each set were adjusted by the Bonferroni test  as well as between “Variation III vs. Variation IV”  (Variation I and III) compared to the VOM (Variation II and IV)   Tables.  and IV) .Effective connectivity from the left IFG to the right HG increased when the original melody of “Twinkle Twinkle Little Star” was significantly modified (VMM), compared with that when the original melody was intact (VOM). It appeared consistent in two different sets with the same rhythmic patterns but with the different melody pattern.The present study employed real music with its variations as musical stimuli, dissected musical elements in each condition, and devised the two comparable sets of conditions, which have the same rhythmic pattern but different melody. Here, we exploited naturalistic conditions in real music instead of devising artificial conditions, and successfully demonstrated how significant variations of melody in real music change a regional connectivity in the human brain. These are distinct from the attempts in previous studies used to original musical pieces , 28–31.An fMRI study, using a real music of “Adios Nonino”, studied the effects of motif repetitions on effective connectivity changes. Specifically they found that the hippocampal connectivity is modulated by motif repetitions, showing strong connections with working memory-relevant areas . This stWhen hearing real music the brain regions would interact to support complex cognitive processes , 33. In The left IFG is also involved in the retrieval of working memory  and episVariation I vs. II” and “Variation III vs. IV”, which are different in the rhythmic patterns of 16th and 8th notes sequences, respectively. Generally the beta frequency band is associated with the processing of deviant stimuli [Also it is interesting that the change in fronto-temporal connectivity was observed in the beta frequency band  was set based on the “C5—C5—G5—G5—A5—A5—G5—G5” motif of “Twinkle Twinkle Little Star” song in the melodies . TherefoConnectivity results in the two sets of conditions, with different rhythms, showed similar pattern. The hypothesis of our study was to find a connection that connectivity pattern was consistent for the two sets of “VOM and VMM” of the different rhythmic pattern. Therefore, the results would be by pitch rather than rhythm. Therefore, it would be natural that rhythmic affects are excluded from our results. Furthermore, the one that influenced the results could be eventually be dismissed as “original melody and modified melody” that encompasses all of familiarity, the stimuli characteristics, and the variation identification.There are several limitations in our study. The present study was limited to 4 regions of interest, including bilateral inferior frontal and superior temporal area. There should be further studies covering the whole brain. For current findings targeting non-musicians, comparative studies involving musicians are needed. Finally, in order to focus on melody difference, we tried our best to eliminate the effects of other elements implied in naturalistic conditions. However, it should be discovered through further studies.In conclusion, the fronto-temporal connectivity from the left IFG to the right HG was enhanced when the modified melody was presented, compared with the original melody of “Twinkle Twinkle Little Star” in Mozart “Ah! vous dirai-je Maman” KV 265. Our findings show that the modification of an original melody in a real music changes the brain connectivity.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.


Primary infection with human cytomegalovirus (HCMV) is usually asymptomatic and leads to the establishment of lifelong latent infection. A major site of latency are the CD34+ hematopoietic progenitor cells. Importantly, normal cellular differentiation of CD34+ cells to a macrophage or dendritic cell phenotype is concomitant with viral reactivation. Molecular studies of HCMV latency have shown that the latent viral genome is associated with histone proteins and that specific post-translational modifications of these histones correlates with the transcriptional activity of the genome arguing that expression of key viral genes that dictate latency and reactivation are subject to the rules of the histone code hypothesis postulated for the regulation of eukaryotic gene expression. Finally, many studies now point to a key role for multiple signaling pathways to provide the cue for HCMV reactivation. The challenge now is to understand the complex interplay between cell identity, transcriptional regulation and cell signaling that occurs to promote reactivation and, additionally, how HCMV may further manipulate these events to support reactivation. Understanding how HCMV utilizes these pathways to drive HCMV reactivation will provide new insight into the mechanisms that govern viral and host gene expression and, potentially, illuminate new, host-directed, therapeutic opportunities to support our attempts to control this important medical pathogen of immune-compromised individuals. Human cytomegalovirus (HCMV), a large DNA virus, is a member of the herpesvirus family. Like all herpes viruses, HCMV has the capacity to establish lifelong latent infections of the host. The simplest definition of viral latency is defined as the persistence of the viral genome in the cell with an absence of lytic replication and virion production but the genome retains the capacity to reactivate and re-enter the lytic lifecycle when specific conditions are met.Reactivation poses a unique set of problems for any virus capable of establishing latency. Upon primary infection, the virion delivers many pre-formed proteins into the cell that play key roles during the initial stages of infection: These incoming proteins transactivate viral gene expression and also disable cell-autonomous immune functions that otherwise would limit infection ,2. Thus (i)A major site of HCMV latency are the hematopoietic progenitor cells resident in the bone marrow which give rise to cells that populate the blood .(ii)The carriage of latent viral genomes is predominantly in cells of the monocyte/myeloid lineage which culminates in viral reactivation in the macrophage and dendritic cell (DC) lineages ,9–16.(iii)In natural latency, multiple copies of the HCMV latent genome persist as circularized, episomal genetic units in the nucleus of the host cell . Further(iv)The association with chromatin is dynamic. Specifically, it has been demonstrated that the MIEP is associated with transcriptionally repressive chromatin in latently infected cells but, in cells that support reactivation, the histones at the MIEP are acetylated consistent with the transcriptional activity observed ,18–20.(v)Inflammation  promotes HCMV reactivation in multiple models of HCMV latency ,11,21–24Accordingly, it is hypothesized that viral genomes are regulated by chromatin structure and, specifically, host cell changes associated with cellular differentiation of myeloid progenitor cells into DCs or macrophages are likely responsible for promoting the post-translational modification of histones required for gene expression to occur. Furthermore, these changes are driven by the activity of host cell signaling pathways. Essentially, the viral genome has become subject to the same mechanisms governing the differential regulation of eukaryotic gene expression that also occurs in a cell type and ligand-specific manner.A wealth of studies from multiple groups have led to a model of HCMV latency and reactivation that is dependent on many important observations:In this short review, I will briefly introduce the evidence that supports the importance of host cell signaling which, when acting in concert with host cell differentiation, promotes viral lytic gene expression and reactivation. Although the focus is on the role of Src family kinase (SFK) signaling in interleukin-6 (IL-6) induced reactivation, I will also discuss the importance of viral gene products in manipulating multiple cell signaling pathways for the establishment of latency and, subsequently, demonstrate the increasing complexity that underpins the molecular mechanisms controlling HCMV reactivation.The work of our laboratory has focused on delineating host functions important for HCMV reactivation. Our studies are predicated on the assumption that the latent HCMV genomes are under the same constraints of the host genetic material and, therefore, likely subject to the same host-mediated mechanisms of gene regulation. Indeed, the demonstration that the latent viral genome is associated with chromatin in naturally infected individuals provides a clear mechanism for the control of HCMV latency and reactivation . A reducIn support of this concept is the observation that the chromatin signature associated with the viral genome at the MIEP correlates with the pattern of gene expression observed . SpecifiThus central to understanding the mechanisms governing HCMV reactivation was to first identify the triggers of HCMV reactivation in differentiated myeloid cells.The first clues that inflammation-associated cell signaling was likely important for viral reactivation came from many studies performed over 20 years ago. The demonstration that both CD34+ progenitors, granulocyte-macrophage progenitors and CD14+ monocytes were sites of HCMV latency ,13,14,27in vitro and ex vivo [To identify potential host mechanisms important for HCMV reactivation we focused on inflammation-associated signaling in DCs — a cell type that supports HCMV reactivation  ex vivo ,16,21. T ex vivo . In turn ex vivo ,30. The  ex vivo . Additio ex vivo . Thus MSin vivo. Indeed, in bone marrow transplant patients over 80% of seropositive transplant recipients will have evidence of HCMV viraemia which, if left untreated, can cause severe morbidity [in vivo given the right signal or, indeed, the right signals. Historic studies demonstrated that TNF-α was pro-reactivation — which was hypothesized to promote the recruitment of the NF-κB transcription factor to the MIEP [Clinical studies quite clearly demonstrate the importance of HCMV reactivation orbidity . The frethe MIEP . Indeed,the MIEP ,34.in vitro suggesting that this pathway actively supports latency [Additionally, Pi3K signaling has been linked to the regulation of HCMV reactivation through the activity of a virally encoded latent gene product, UL138 . This pr latency . Interes latency . This wa latency . Intrigu latency  and, pot latency . In the  latency . Both thFor the purpose of this review, however, is the more general implication that the study of any specific cell signaling pathway often has to be considered within the framework of the signalsome in the host cell. Thus understanding the context in which a signaling pathway is being activated becomes crucial. Signaling does not occur in isolation whereby it is highly likely that more than one pathway is going to be important for the outcomes you are analyzing — particularly given the clear cross-talk that exists within signaling pathways.In our initial studies of HCMV reactivation, we remained puzzled by the observation that ERK–MAPK signaling promoted reactivation in a cell type-dependent manner ,44. ERK–To address this, we tested whether ERK–MAPK alone was sufficient to induce reactivation. Ectopic activation with a constitutively active version of MEK (the upstream kinase of ERK) failed to robustly promote reactivation supporting the concept that the cellular context of the ERK–MAPK signaling was important . Here ouper se.The SFKs comprise nine members: Src, Yes, Fgr and Fyn (subfamily A), Hck, Lck, Blk and Lyn (subfamily B) and Yrk . SFKs arThe phospho-proteomics performed in DCs and LCs  revealedHck exists in two isoforms generated from a single transcript — a lysosome-associated form and plasma membrane-associated form are evident in cells . InactivThe implication that Hck activity potentiated ERK–MAPK signaling potentially explained the reactivation phenotype in DCs. However, this view was tempered by the MEK overexpression data which argued that simply high levels of ERK signaling was not the driving factor . Indeed,We had previously demonstrated that ERK–MAPK activity promoted histone phosphorylation at the MIEP and implicated this event in reactivation . In HSV,Studies of the chromatin phenotype at the MIEP and, specifically, how it changed with time in response to IL-6 proved instructive when analyzed in the context of data that measured the impact of HAT inhibitors on HCMV reactivation. What became evident was that whilst ERK–MAPK promoted histone phosphorylation at the MIEP, subsequent de-methylation and histone acetylation was impacted by a second pathway which was revealed to be SFK dependent . Thus whInterestingly, the identification of a role for SFK activity during HCMV reactivation became more intriguing in light of emerging data arguing that the virus itself was not a passive observer in the process of latency and reactivation. Very recently it has been shown that an HCMV gene product, UL7, binds to flt3 ligand receptor to drive myelopoiesis and HCMV reactivation . An impoA second viral gene product, US28, encodes for a GPCR that can modulate cell signaling pathways during both latent and lytic infection ,57. FascHowever, this impact on cell signaling was not uniform for all pathways of interest and specifically US28 did not appear to inhibit SFK signaling in the original study . Indeed,gp130 is crucial for reactivation-specific signaling events. Indeed, the sequestration of Hck signaling by US28 in latently infected cells may result in reducing the availability of Hck for reactivation. Furthermore, the up-regulation of Hck in DCs thus could increase the availability of Hck for IL-6 signaling and thus reactivation may explain the propensity for reactivation to occur more efficiently in DCs. These hypotheses are easily testable and will provide new insight into HCMV reactivation and also the complexity associated with cell-type-specific signaling events.In the context of HCMV latency and reactivation, the up-regulation of SFK activity appears counter-intuitive. One potential explanation is that simply the activation of a signaling pathway is not the only important event but also the nature of the stimuli and thus the ligand:receptor pathway responsible for Hck activation. As stated above, Hck activation occurs in response to many ligands and, potentially, the nature of the stimuli dictates the downstream events it triggers . ActivatThe co-evolution of HCMV with the host has rendered the virus an integral component of the signaling events in the latently infected cell. This is evidenced by both a clear responsiveness to host driven cues of inflammation and cellular differentiation as well as the expression of viral gene products to further manipulate the activity of key pathways in the cells. What studies of HCMV latency exemplify is the complexity associated with interpreting the role of cell signaling pathway activity in the control of HCMV and, by extension, eukaryotic gene expression.Is complexity in the signaling pathway usage indicative of a requirement to activate multiple promoters  for HCMVHow does Hck and SFK signaling dictate the recruitment of HAT activity? Is an intermediary required?How important is the nature of the stimulus that activates Hck/SFK activity? Specifically, is Hck pro-reactivation only via gp130 receptor engagement?Can inhibition of Hck-specific functions associated with HCMV reactivation be tolerated by the host cell? Targeting host functions dramatically raises the barrier to the development of drug resistance in viral infections and thus may prove useful for future strategies to control HCMV reactivation in susceptible patient populations.


However, the fertility rate has decreased dramatically from 6.24 in 1975 to 3.95 in 1995 and 1.72 in 2016 7. The main objective of these policies is to develop a pattern of domestic economic on the basis of social values and norms, national resources and highly qualified workforce in order to reduce the vulnerability of the country against international sanction and even turn these pressures into opportunities. This is a paradoxical and sophisticated issue. On the one hand, Iranian population is aging due to low fertility rates, therefore, we need to increase the fertility rate above the replacement fertility level. On the other hand, we need to improve the economic status, inversely associated with fertility rate. In other words, gross domestic product increases as total fertility rate decreases and vice versa8 (In February 2013, the general policies of "resistance economy" were issued by the supreme leader of Iran, including 24 clausese versa8 .There is no doubt that fertility rate should increase above the replacement level, but we have to define a stringent population policy and determine an accurate level of replacement fertility to reach a sustainable population with reasonable growth rate. In such situation, we may expect to have a progressive economic and provide a "resistance economy" against international sanction; otherwise, we will back to the past two decades with unpredictable and unplanned population growth that may result in substantial and inevitable damage to the economic growth.The author declares that there is no conflict of interest.