Hepatozoon spp. are Apicomplexan protozoa that parasitize a wide diversity of vertebrate hosts. In Brazil, few studies have reported the occurrence of Hepatozoon spp. in rodent species. Additionally, an evaluation of the population structure and distribution of Hepatozoon species over several Brazilian biomes has not yet been performed. The present work aimed to investigate the genetic diversity of Hepatozoon spp. in rodents from 31 genera sampled in five Brazilian biomes. Samples were submitted to PCR assays for Hepatozoon spp. targeting two regions of the 18S rRNA gene. Infection by Hepatozoon spp. was detected in 195 (42.2%) rodents comprising 24 genera. Phylogenetic analyses of 18S rRNA sequences grouped all sequences in the clade of Hepatozoon spp. previously detected in rodents and reptiles, apart from those detected in domestic/wild carnivores. These data raise two non-exclusive hypotheses: (i) rodents play an important role as intermediate or paratenic hosts for Hepatozoon infections in reptiles; and (ii) rodents do not seem to participate in the epidemiology of Hepatozoon infections of domestic/wild canids and felids in Brazil. TCS analyses performed with available 18S rRNA Hepatozoon sequences detected in rodents from Brazil showed the occurrence of six haplotypes, which were distributed in two large groups: one from rodents inhabiting the coastal region of Brazil and Mato Grosso state, and another from rodents from the central region of the country. A wide survey of the South American territory will help to elucidate the evolutionary history of Hepatozoon spp. parasitizing Rodentia in the American continent. Hepatozoon belongs to one of the six genera of blood parasites known as hemogregarines, which have a heteroxenous life cycle involving an intermediate vertebrate host and a blood feeding definitive invertebrate host. Studies have detected the presence of Hepatozoon species in domestic and wild mammals, birds, reptiles, and amphibians1.The genus Hepatozoon spp. warrants investigation to evaluate whether genotypes of Hepatozoon spp. circulating in rodents are specific to this group of mammals, or if there are genotypes shared between this group of mammals and wild carnivores or reptiles. In the latter scenario, rodents might play an important role as intermediate or paratenic hosts for species of Hepatozoon.The epidemiology of hepatozoonosis in wild and domestic animals in Brazil has not been fully elucidated. The role of rodents in the epidemiology of Hepatozoon ayorgbor. Experimental transmission to snakes was achieved when these animals were fed rodent tissues infected with H. ayorgbor2. For mammals, dogs from rural areas often live in areas surrounding woods and might predate Hepatozoon-infected rodents3. Several studies performed in the USA have demonstrated that H. americanum can be transmitted by predation of rodents and lagomorphs6. In the African continent, Maia7 suggested that wild carnivores can become infected by Hepatozoon sp. through predation of rodents.Predation might represent an important transmission route for Hepatozoidae protozoa. For instance, predation is an important route for reptile infections by Hepatozoon infecting rodents in several regions around the world, studies aiming at analyzing the genetic diversity and phylogeography of these apicomplexan protozoa are scarce. In Brazil, few studies have reported the occurrence of Hepatozoon spp. in rodent species12. Additionally, the population structure, the distribution of Hepatozoon species over several Brazilian biomes, and how it reflects into the parasite evolution have not yet been assessed. The present study aimed to investigate the occurrence of Hepatozoon spp. in wild rodents from several regions of Brazil. Additionally, this work aimed to evaluate the genetic diversity of haplotypes in sampled rodents to draw genetic and geographical inferences across the Brazilian territory.Despite the molecular confirmation of irbp gene (endogenous control of reaction). The ten samples negative for the irbp-PCR assay were also negative in the cPCR based on the gapdh gene and were excluded from subsequent analysis. The average concentration of DNA was 154.62 ng/µL (0.1 to 812.0 ng/µL), and the 260/280 ratio was 1.95 (0.7 to 6.18).Among the 472 rodent spleen samples analyzed, 462 were positive for the amplification of a fragment of the Hepatozoon spp., amplifying in one or both regions of 18SrRNA gene (based on protocols described by Perkins and Keller13 and Ujvari14)  were considered positive for Hepatozoon spp. based on the first 18SrRNA gene region analyzed (according to the protocol described by Perkins and Keller13)  by BLAST analysis. Eight sequences showed 100% identity with Hepatozoon sp. detected in Amblyomma fuscum (KU955319) collected from a rodent Akodon montensis in Santa Catarina, south Brasil. One sample showed 99% identity with Hepatozoon sp. detected in a rodent Oecomys marmorae (KX776332) sampled in Brazilian Pantanal. Lastly, one sample showed 99% identity with Hepatozoon sp. from a Caiman crocodilus (MF322539) sampled in Brazilian Pantanal.Of the 462 rodents analyzed, 69 14.93%) were positive for 4.93% werHepatozoon spp. based on the second 18SrRNA gene region analyzed (according to the protocol based on the 18S rRNA gene described by Ujvari14)  showed 98–100% identity with Hepatozoon sp. detected in the rodent Akodon sp. (KU667308) sampled in Brazil . One sequence (MH111418) showed 100% identity with Hepatozoon sp. detected in a snake (Psammophis schokari) (KX453646) sampled in Omã, on the southeastern coast of the Arabian Peninsula. One sequence (MH111404) showed 100% identity with Hepatozoon sp. detected in a snake  (KX387861) sampled in Spain. Lastly, one sample (MH111421) showed 100% identity with Hepatozoon sp. detected in a rodent (Thylamys macrurus) (KX776354) sampled in Pantanal, Mato Grosso do Sul, Brazil.Of the 462 rodents analyzed, 172 (37.2%) were positive for Hepatozoon spp. 18SrRNA sequences obtained from both PCR protocols separately and concatenated presented similar results . The second grouped sequences of H. canis and Hepatozoon spp. detected in domestic and wild canids; (iii). The third branch composed of H. americanum and Hepatozoon spp. detected in domestic and wild felids and canids. The clades showed considerable statistical support. Haemogregarina spp. sequences were used as an outgroup. Figure Hepatozoon spp. 18SrRNA using sequences detected in this study and other sequences deposited in GenBank (using ML method).The phylogenetic inferences estimated by both Maximum Likelihood (ML) and Bayesian methods of Hepatozoon spp. 18SrRNA sequences obtained from both PCR protocols showed a high degree of heterogeneity revealing two major clusters: (i) Hepatozoon spp. sequences obtained from rodents and reptiles; (ii) Hepatozoon spp. sequences obtained from canids and felids . This fragment showed two haplotypes, with haplotype diversity (Hd) = 0.1538 and number of variable sites (S) = 2. For the second fragment14, seventeen sequences presented good alignment (fragment of 277 bp). This fragment showed a higher diversity, with five haplotypes [haplotype diversity (Hd) = 0.426], nucleotide diversity (Pi) = 0,00453 and number of variable sites (S) = 9. Haplotype #1 was the most geographically distributed and was detected in a relatively higher number of rodent species present in the states of São Paulo, Rio de Janeiro, Bahia, and Ceará. Haplotype #2 was represented by one sequence detected in the state of São Paulo. Similarly, haplotypes #3, #4, and #5 were represented by one sequence each, detected in the states of Mato Grosso and Goiás state (#5) Hepatozoon spp. 18S rRNA sequences detected in rodents from other studies performed in Brazil10. Twenty-six sequences were selected, and the analysis was performed with the TCS software v.1.2116  were not linked with the other sequences and were grouped separately, forming another haplogroup (using a 95% parsimony threshold).Additionally, a haplotype network analysis was carried out using 116 Fig. . These s116 Fig.  and 5. THepatozoon sp. haplogroups. We tested one hierarchy construction segregating the haplogroups according to geographic location, one from the coastal region of Brazil and Mato Grosso state and another from the central region of Brazil  was performed to evaluate the degree of genetic structure among zil Fig. . The reszil Fig. .Table 1AHepatozoon sp. in wild and domestic animals is still not fully elucidated around the world. The role of rodents in the epidemiology of Hepatozoon sp. should be further investigated to evaluate if genotypes circulating in rodents are specific of this group of mammals or might also circulate in wild carnivores and reptiles; in the latter case, rodents would play a role as intermediate or paratenic hosts in the epidemiological cycles.The epidemiology of Hepatozoon spp. in several rodent species trapped in five Brazilian biomes: Cerrado, Pantanal, Amazon, Caatinga, and Atlantic Forest. Hepatozoon sp. DNA was detected in 24 different rodent genera in one or both PCR protocols based on the 18S rRNA gene. The percentage of positive animals and genera found in the present study was superior to that reported in previous works performed in Brazil10. This study provides the first report of the occurrence of Hepatozoon spp. in Rattus rattus, Mus musculus, Proechimys roberti, P. cuvieri, Galea spixii, Hylaeamys megacephalus, Gracilinanus agilis, Cerradomys scotti, C. akroai, C. marinhus, and Wiedomys cerradensis. Also, the positivity of rodents for Hepatozoon spp. was reported, for the first time, in the states of Bahia and Ceará, northeastern Brazil, Santa Catarina (South), Rio de Janeiro (Southeast), and Tocantins . Herein, a moderately high positivity for Hepatozoon was found among trapped rodents, with a description of the parasitism, for the first time, in certain species and localities not previously investigated. It is likely that the wide sampling, with 472 rodents collected in five Brazilian biomes, with diverse climatic and environmental characteristics, has influenced these results.The present study showed the occurrence of query coverage and identity values (98–100%) for sequences of Hepatozoon spp. detected in rodents, reptiles, and ticks previously described in Brazil and other countries. BLAST and phylogeny  analyses yielded similar results for both 18S rRNA protocols . The sequences detected in rodents in the present study were positioned in a large clade comprising Hepatozoon sequences previously detected in rodents and reptiles. Hepatozoon sequences from felids and canids were grouped in another large clade. These results corroborate with previous studies. Hepatozoon sequences detected in rodents in Slovakia and the Czech Republic were phylogenetically related to sequences detected in lizards and snakes, positioning apart from H. canis detected in dogs17. Similar results were obtained by Sousa10 when analyzing Hepatozoon sequences from rodents sampled in Brazilian Pantanal. These results suggest that rodents might play an important role as intermediate or paratenic hosts for Hepatozoon infections in reptiles; in contrast, these mammals do not seem to participate in the epidemiological cycles of Hepatozoon species parasitizing domestic and wild canids and felids in Brazil. In South Africa, one sequence of 18S rRNA Hepatozoon sp. detected in Vulpes pallida was closely related to Hepatozoon sequences detected in rodents (Jaculus sp.), reptiles, and marsupials from other localities7. Therefore, future studies should be conducted to investigate the real role of rodents in the epidemiology of canine hepatozoonosis in the African continent.The sequences detected in rodents in the present study presented high 18. The haplotype diversity found in rodent-associated Hepatozoon 18S rRNA sequences in the present study was higher than those found in previous studies performed in Brazil. For instance, Gomes19 found four Hepatozoon 18S rRNA haplotypes in capybaras (Hydrochoerus hydrochaeris) in Marajó Island, northern Brazil. In Pantanal wetland, central-western Brazil, three Hepatozoon 18S rRNA haplotypes were found in rodents (T. fosteri) based on Ujvari’s PCR protocol14. When the same analysis was performed using Hepatozoon 18S rDNA sequences originated from Perkins and Keller’s PCR protocol13, four haplotypes were detected10. In the present study, among sequences obtained from Perkins and Keller’s PCR protocol13, only two haplotypes were detected, and among 17 sequences obtained from Ujvari’s PCR protocol14, five haplotypes were detected. Based on these results, we suggest that the Hepatozoon 18S rDNA haplotype analyzed in rodents should be performed based on sequences obtained from Ujvari’s PCR protocol14.Haplotype diversity is controlled by multiple processes, such as mutation, recombination, and demographyHepatozoon spp. described up to now in Brazil. For this purpose, 26 sequences from different localities were chosen from the present study  and previous studies performed in the states of São Paulo11, Mato Grosso8, and Mato Grosso do Sul10. As a result, six haplotypes were detected among the 26 sequences, showing a significant heterogeneity of Hepatozoon sp. parasitizing this group of mammals. The existence of two large haplogroups between the 26 sequences was noticed as part of the TCS analysis. The two haplogroups presented a high level of genetic structure when compared in AMOVA. The FST value (0.7267), which was statistically significant, was sufficient to conclude that there is a difference between these two haplogroups; FST values higher than 0.25 characterize a strong pattern of genetic structuring20. Additionally, sequences detected in rodents from Mato Grosso do Sul were grouped separately, forming another haplogroup. Apparently, there are two distinct groups of haplotypes circulating in rodents in Brazil, one from the coastal region and Mato Grosso state and another from the central region of Brazil, with the sequences from Mato Grosso do Sul being relatively more distinct. To expand this primary analysis, new studies in Brazil should be performed, covering a larger number of rodent species and geographic region.Unlike in previous studies, the present work analyzed the diversity of 18S rDNA haplotypes of Hepatozoon species diversity21. Although the 18S rDNA gene has been commonly used as a molecular marker for phylogenetic analyses, problems in separating closely related species might occur due to its high degree of conservation22. Mitochondrial genomes have been used to help unravel the complex phylogenetic relationship of piroplasmids23. Similarly, H. canis mitochondrial genome sequences have been recently described using next-generation sequence approaches24. Therefore, mitochondrial genomes should be used in the future as a barcode for discriminating Hepatozoon haplotypes and species that are shown to be closely related in phylogenetic inferences based on 18S rRNA. Additionally, the complete genome of H. canis24 will open opportunities to identifying novel target genes, allowing better discrimination of Hepatozoon haplotypes circulating in different animal species and vectors. Such an approach would contribute to a better definition/description of Hepatozoon species, epidemiological cycles, and trophic relationships.Until recently, 18S rDNA gene sequences comprised the only molecular markers for the analysis of Sampling procedures were approved by the “Brazilian Institute for Environment and Natural Renewable Resources” (IBAMA) (IBAMA/CGFAU/LIC 3665-1) and by the Ethics Committee of Oswaldo Cruz Foundation (FIOCRUZ)  and all experiments were performed in accordance with CGFAU and CEUA FIOCRUZ guidelines.25. Sampling places were chosen by convenience. Animals were caught using Tomahawk and Sherman “live-traps” during previous studies performed by the Laboratories of Trypanosomatid Biology and Biology and Parasitology of Wild Mammals Reservoirs Laboratories, Oswaldo Cruz Institute, Rio de Janeiro, Brazil27. Euthanasia of the sampled mammals was performed for taxonomic identification and/or diagnosis of parasites. Rodents were exsanguinated after anesthesia with intramuscular ketamine hydrochloride (100 mg/mL) and acepromazine (10 mg/mL), and euthanasia was assured by intracardiac injection of potassium chloride .Between 2000 and 2011, multiple rodent genera [n = 31] were trapped in five Brazilian biomes: Amazon, Cerrado, Atlantic Forest, Caatinga, and Pantanal Fig. 25. Sampl®, Valencia, California, USA), according to manufacturer’s instructions. The DNA concentration and absorbance ratio (260/280 nm) were measured using a spectrophotometer .Spleen tissues from 472 rodents were collected and stored in DNase- and RNase-free microtubes containing ethanol and maintained at −20 °C until DNA extraction. DNA was extracted from 10 mg of each rodent spleen tissue using the DNeasy Blood and Tissue Kit (Qiagenirbp (“interphotoreceptor retinoid-binding protein”) gene as an internal control28. Samples negative for the above PCR protocol were tested in another cPCR targeting the mammal gapdh gene29. Samples negative for both protocols were removed from subsequent analyses.To evaluate the quality of the extracted DNA, each spleen DNA sample was tested by a conventional cPCR targeting the mammal Hepatozoon spp. based on the Perkins and Keller (targeting a fragment of 800 bp)13 and Ujvari14 (targeting a fragment of 600 bp) protocols. Rodents were considered positive for Hepatozoon spp. when samples amplified the target region in one or both protocols. In samples positive for both of the above PCR protocols, the two Hepatozoon 18S rRNA sequences obtained were concatenated to obtain a large 18S rRNA fragment to be used in phylogenetic analyses (approximately 1400 bp). Hepatozoon caimani DNA obtained from a naturally infected Caiman crocodilus yacare30 was used as a positive control. Ultra-pure sterile water  was used as a negative control in all PCR assays. The results were visualized in 1% agarose gel stained by ethidium bromide solution. Only amplicons showing high-intensity bands in agarose gel electrophoresis were sequenced. The amplified products were purified using the Silica Bead DNA gel extraction kit , following the manufacturer’s protocol. The sequencing of the two different regions of 18S rRNA Hepatozoon gene fragments was carried out using ABI PRISM 310DNA Analyzer 31. The quality of the obtained sequence electropherograms was checked by Phred-Phrap software version 23, and the quality of each nucleotide sequence was observed33. Each nucleotide was checked for a score and was considered of good quality when scoring Phred >20. Additionally, the presence of a double read in each nucleotide was evaluated. Consensus sequences obtained by the alignment of the sense and antisense sequences were constructed using the same software34. The BLAST program was used to analyze the sequences of nucleotides, aiming to browse and compare with sequences from the GenBank international database35. All sequences that showed appropriate quality standards (query coverage >90%) and identity with Hepatozoon spp. were deposited in GenBank. Samples showing positive results for both PCR protocols had their sequences concatenated. The obtained sequences were aligned with those retrieved from GenBank using MAFFT software, version 715. Sequences used for phylogenetic inferences were selected from BLAST results and other studies performed in Brazil and other countries  simulations were run for 106 generations with a sampling frequency of every 100 generations and a burn-in of 25%. The number of generations was selected based on the value of the average standard deviation of split frequencies  . The best model of evolution was selected by the program jModelTest2 (version 2.1.6) on 11 XSEDE19, under the Akaike Information Criterion (AIC)37. ML analysis was performed with cluster Blackbox RaxML38. All phylogenetic analyses were performed using the CIPRES Science Gateway39. The phylogenetic tree edition and rooting (outgroup) were performed using the Treegraph 2.0 beta software40. Nucleotide sequence genealogies were inferred by Network analyzes using Splitstree v4.11.3 software using sequences detected in the present study and sequences deposited in GenBank from other studies41. A haplotypic network using the software TCS16 with a 95% parsimony threshold was performed to infer the distance between haplotypes and connection between its occurrence and geographic areas. The molecular variance (AMOVA) analysis was performed using Arlequin v.3.1142, including all haplogroups observed in the haplotypic network.Two different PCR protocols were used aiming at amplifying different regions of 18SrRNA of Sampling procedures were approved by the “Brazilian Institute for Environment and Natural Renewable Resources” (IBAMA) (IBAMA/CGFAU/LIC 3665-1) and by the Ethics Committee of Oswaldo Cruz Foundation (FIOCRUZ) .Supplementary info


Wnt ligands interact with the transmembrane cell surface receptors Frizzled and ROR/RYK to initiate complex signaling cascades that are crucial for cell physiology and the proper functioning of the immune system. Wnt signaling is instrumental in maintaining immune surveillance and during infections by pathogenic microbes helps mount host resistance to infection. Some pathogens, however, utilize Wnt signaling to build a niche for their survival. The goal of this review is to summarize current and developing concepts about the tug of war between Wnt signaling and pathogens for deployment of host resources, focusing mostly on macrophages and cytoskeletal actin dynamics. An additional objective is to outline the interrelation between Wnt signaling and the host microbiota, which is vital for immune defense, discussing in the same perspective, how Wnt signaling could be differentiating pathogen from non-pathogen. Macrophages, major sentinels of immune defense utilize the Wnt signaling scheme to sustain immune homeostasis, maintain immune surveillance, and combat infections with several pathogens. Some microorganisms, however, outmaneuver Wnt signaling and exploit it to create a niche for their survival. Wnt associated cytoskeletal modulations and transcriptional programs partake of such host pathogen interactions –8. Wnt sWnt proteins constitute a family of about 19 different secreted cysteine-rich glycoproteins in mammals, which are highly conserved among different species. Nusse et al. first identified the mammalian counterpart of Drosophila Wingless and termed it Wnt1, which nomenclature wise is a combination of Drosophila Wingless and the mouse proto-oncogene Int1 –13. The Wnt signaling can be categorized into two main classes—canonical (β-catenin dependent) and non-canonical (β-catenin independent). In canonical Wnt signaling, β-catenin, which accumulates in the cytoplasm, enters into the nucleus acting as a transactivator for LEF/TCF transcription factors to initiate expression of β-catenin responsive genes . In non-Although it is now clear that Wnt signaling is closely associated with infection, sustenance of host microbiota and immune regulation –6, 9, inWnt signaling in macrophages plays a crucial role in shaping the outcome of infections by different pathogens , 41–43. Pseudomonas sp. and Streptococcus sp. is inhibited by Wnt signaling. Wnt induced bacterial clearance in macrophages occurs by phagocytosis and subsequent xenophagy through utilization of the host actin associated autophagy circuit. In this context, the function of Wnt5A, which mediates cytoskeletal actin modulations through activation of the actin associated proteins Rac1 and Disheveled holds considerable significance  causing bacterium sheveled . Blockadnfection , suggestMycobacterium species. Mycobacterial infections are associated with altered expression of several Wnts  that synchronize with host immune programs against infections –81. In t propria . These m propria , 83, 84. propria , 85.Wnt signaling is important for gut organogenesis , 87 and Complex Wnt signaling schemes that are intrinsically associated with macrophage mediated immune functions  conform to the in-built maneuvering of macrophages as they confront with different kinds of pathogens , 91. SevIn future, the influence of Wnt signaling on actin modulations at the initial stages of infection needs to be deciphered at the molecular level in the context of different microbes, ranging from virulent pathogens to the resident microbiota, which may be deemed as non-pathogens. Additionally, the potential links between the cytoskeletal actin dynamics and transcriptional programs need to be carefully assessed. In this connection, a good understanding of the cytokine milieu that correlates with the interaction of Wnt signaling with different microbial infections will be important, especially in view of its connection with the different stages of sepsis associated with pathogenic infections . A thoroMS organized the layout of the article and wrote the article. DN contributed to the layout organization and writing. SJ and TS worked on the table and references and assisted in writing.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. The reviewer JM declared their collaboration with one of the authors MS as co-editors in the Research Topic and confirmed the absence of any other collaboration to the handling editor.


Plasmodium falciparum merozoite EBL ligands have been identified: erythrocyte-binding antigen-175 (EBA-175), erythrocyte-binding antigen-181 (EBA-181), erythrocyte-binding ligand-1 (EBL-1) and erythrocyte-binding antigen-140 (EBA-140). It is generally accepted that glycophorin A (GPA) is the receptor for P. falciparum EBA-175 ligand. It has been shown that α sialic acid residues of GPA O-glycans form conformation-dependent clusters on GPA polypeptide chain which facilitate binding. P. falciparum can also invade erythrocytes using glycophorin B (GPB), which is structurally similar to GPA. It has been shown that P. falciparum EBL-1 ligand binds to GPB. Interestingly, a hybrid GPB-GPA molecule called Dantu is associated with a reduced risk of severe malaria and ameliorates malaria-related morbidity. Glycophorin C (GPC) is a receptor for P. falciparum EBA-140 ligand. Likewise, successful binding of EBA-140 depends on sialic acid residues of N- and O-linked oligosaccharides of GPC, which form a cluster or a conformational structure depending on the presence of peptide fragment encompassing amino acids (aa) 36–63. Evaluation of the homologous P. reichenowi EBA-140 unexpectedly revealed that the chimpanzee homolog of human glycophorin D (GPD) is probably the receptor for this ligand. In this review, we concentrate on the role of glycophorins as erythrocyte receptors for Plasmodium parasites. The presented data support the long-lasting idea of high evolutionary pressure exerted by Plasmodium on the human glycophorins, which emerge as important receptors for these parasites.Glycophorins are heavily glycosylated sialoglycoproteins of human and animal erythrocytes. In humans, there are four glycophorins: A, B, C and D. Glycophorins play an important role in the invasion of red blood cells (RBCs) by malaria parasites, which involves several ligands binding to RBC receptors. Four  Glycophorins, major sialoglycoproteins of human and animal erythrocytes, are transmembrane type 1 glycoproteins with relatively low molecular weight 20–30 kDa), carrying sialylated O-glycans and/or N-glycans 0–30 kDa,. Human eGlycophorins carry blood group antigens, including MN, Ss and Gerbich , 2. MostPlasmodium parasites. In particular, genome-wide association studies have shown that resistance to malaria may be connected with human glycophorin ABE locus  is of particular interest when novel malarial therapeutics are considered. Indeed, it was shown that the sugar moiety, 2,3-didehydro-2-deoxy- 100 μM) . Moderatseverity , 44.D 0.26 μm whereas a recombinant RII fragment alone bound GPA with a lower affinity . In. InP. faP. falciparum culture supernatant did not bind to S-s-U- RBCs. Moreover, EBL-1 ligand failed to bind to RBCs treated with chymotrypsin, which cleave GPB and neuraminidase, which removes sialic acid residues [The early experiments showed that peptide fragments of EBL-1 merozoite ligand bound on human RBC membrane to a protein with an apparent molecular weight of 36 kDa . It was residues . Thus, Gresidues  and the residues . This firesidues .P. falciparum invasion came from screening of the merozoite and human RBC proteomes [Similar to EBA-175 the RII region of EBL-1 ligand contains two DBL domains, F1 and F2. The major binding site of EBL-1 for GPB was identified within its 69-amino acid segment (F2i) of its F2 domain . Both F1roteomes . Of 13 proteomes .ex vivo cultured erythrocytes (cRBCs) with decreased expression of GPA, GPB or GPC, it was shown that most laboratory strains and field isolates of P. falciparum require GPB for invasion [P. falciparum invasion is in contradiction to the fact that some laboratory strains have mutated or deleted the ebl-1 gene [Recently, using invasion . In the l-1 gene .P. falciparum caused selection for this polymorphism. Thus, the Dantu variant of GPB, which is a hybrid GPB-GPA molecule with a GPB N-terminus and GPA C-terminal region, seems to be responsible for protection against P. falciparum invasion in vitro [GPB-null phenotype is prevalent in the regions where malaria is endemic , suggestin vitro , 69.GPE, GPA and GPB. Moreover, evaluation of genome sequence data from individuals of sub-Saharan descent suggested a strong protective effect of the Dantu (NE type) genotype against cerebral malaria anemia in East Africa [GypE, GypB and GypA glycophorin genes; if translated, the encoded protein joins the extracellular domain of GPB to the transmembrane and intracellular domains of GPA, since GPE is probably not expressed at the protein level [The large genetic association study (GWAS) of malaria, which included over 11,000 African children, revealed a new locus of resistance to severe malaria . It was t Africa . The Danin level . It creaP. falciparum receptors and host Band 3 at the RBC surface [The most recent studies of gene polymorphisms in children in Kenya confirmed that the presence of Dantu mutation was associated with reduced risk of severe malaria by 43% among heterozygotes and 74% among homozygotes, and the protection was equal for all forms of severe malaria. In addition, Dantu seemed to ameliorate malaria-related morbidity . Moreove surface .GYPC gene [Studies on the EBA-140 ligand, which similarly to EBA-175 contains two DBL domains F1 and F2 , showed YPC gene , 77.Fig.P. falciparum EBA-140 in different strains, which have been reported to alter host receptor specificity [P. falciparum have been identified , which encompass four amino acid residues of the R II F1 domain in positions 185, 239, 261 and 285, respectively. These polymorphic variants of EBA-140 R II expressed on the surface of COS cells showed different receptor binding specificity. Of these five variants, only RII from the Dd2/Nm strain  was sensitive to neuraminidase and trypsin treatment of RBCs, and was the only one which did not bind to Gerbich-negative RBCs. A different binding pattern of two RII/EBA-140 polymorphic variants V,S,T,K and V,S,K,K was also confirmed in another study when both RII variants were expressed on the surface of Chinese hamster ovary (CHO-K1) cells [These inconsistencies may be attributed to the polymorphisms within the binding region of cificity . Five po1) cells . It was P. falciparum culture supernatants provided contradictory evidence [P. falciparum strains [On the other hand, a study using native EBA-140 ligands from evidence . All of evidence  or CHO-Kevidence , this st strains .GPC gene (aa 36–63) is of particular significance. However, these results were not confirmed in another study using EBA-140 from 3D7 clone supernatant , since this variant bound to Gerbich erythrocytes with a moderately higher efficiency than normal RBCs [P. falciparum parasites invade Ge-negative cells less efficiently than normal erythrocytes, it is highly possible that selection for this allele has been an evolutionary mechanism of protection against malaria. Determining which fragment of the polypeptide chain of GPC is responsible for binding EBA-140 ligand was the subject of several studies, also in our laboratory where we used RII/EBA-140 expressed in a baculovirus system. It confirmed that the GPC region encompassing aa residues 36–63 is indispensable for EBA-140 ligand binding [A decreased binding of EBA-140 observed in the case of Gerbich-negative erythrocytes –82 implimal RBCs . At the mal RBCs . Since PAnother issue to be solved is the role of the oligosaccharide chains of GPC in EBA-140 binding. The extracellular domain of GPC is believed to have 12 sialylated O-glycosidic chains linked to serine and threonine residues and one complex N-glycosidic chain at Asn8 . It has The turning point in the search for better understanding of the molecular basis of invasion by EBA-140 ligand came with solving the crystal structure of its recombinant binding region , 87. It P. falciparum EBA-175 and P. vivax DBL ligand, the structure of PfEBA-140 RII and its glycan binding mechanism of PfEBA-140 is unique [Plasmodium ligands engage receptors as monomers or dimers is an issue of profound implications for parasite biology and control [In comparison to other RII regions of the DBL family, including homologous s unique . It was s unique , 88. In s unique . The for control .P. falciparum EBA-140 ligand bound neither to Gerbich GPC deletion variant (lacking aa 36–63) nor to GPD (a truncated form of GPC lacking aa 1–21), but did bind to GPC Yus variant (lacking aa 17–35) [P. falciparum endemic region [P. falciparum binding inhibitors for therapy.The structures of GPC N-glycans essential for GPC-EBA-140 binding were elucidated using mass spectrometry . It was a 17–35) . It sugga 17–35) . The cruc region , 84. TheP. falciparum parasite, interesting data recently came from studies using P. berghei. Because there is a significant homology in GPC genes across the species, the mouse GPC homolog was identified as a RBC receptor [P. falciparum EBA-140 ligand in the P. berghei genome was identified. The putative protein called PBANKA-1332700 may serve as ligand for mouse GPC.In addition to the studies with the human receptor . It was receptor . One homin vivo remains unrecognized. It was revealed that GPC mediates rosetting by P. falciparum STEVOR protein [Once the parasite invades RBCs it releases variant surface antigens (var), such as erythrocyte membrane protein 1 (EMP1), STEVOR and RIFIN , 93. Var protein . Indeed,P. falciparum infected RBCs, the general rule applies to P. vivax as well and it may also involve GPC. Surprisingly, rosettes formed by P. vivax occur preferably among normocytes (mature RBCs) and not reticulocytes [P. vivax normally prefers to invade reticulocytes. In addition, a strong inhibition of P. vivax rosette formation by an antibody against the N-terminus of GPC was shown. Thus, GPC seems to function in the rosetting of P. vivax.Although most RBCs rosetting experiments were performed with ulocytes , althougP. falciparum EBA-140 receptor on human RBCs [P. reichenowi EBA-140 ligand binding to chimpanzee RBCs [P. falciparum in humans. This hypothesis needs to be corroborated using EBA-140 ligands from other species of Plasmodium invading Great Apes.As discussed above, there is a general agreement that GPC but not GPD is man RBCs , 97, 98.zee RBCs  unexpectzee RBCs . It may P. vivax that has been lost in many African ethnic groups rendering them resistant to P. vivax infection. Plasmodium falciparum, which causes most malaria cases in Africa, targets heavily glycosylated proteins that cover the surface of human RBCs, named glycophorins. Although GPA, GPB and GPC have been known as P. falciparum receptors for quite some time, data linking their polymorphism with resistance to malaria have been missing. With the identification of specific protective alleles in the glycophorin locus of individuals resistant to severe malaria, glycophorins have moved to the forefront of research on malaria epidemiology. Moreover, these data finally consolidate the long-standing idea that the human glycophorin makeup is a footprint of high evolutionary pressure exerted by Plasmodium parasites. Altogether, glycophorins emerge as not only an important foothold for the parasite on its way into the RBC but also an essential step in our quest to fully understand the Plasmodium biology and design new malaria interventions.Given the high death toll caused by malaria since time immemorial, it is not surprising that human genetic variants that protect against malaria are common in populations living in tropical areas. One example is the sickle cell allele that protects from malaria in heterozygous carriers, or Duffy antigen, which is a receptor for


To understand how neural circuits process information, it is essential to identify the relationship between computation and circuit organization. Rich clubs, highly interconnected sets of neurons, are known to propagate a disproportionate amount of information within cortical circuits. Here, we test the hypothesis that rich clubs also perform a disproportionate amount of computation. To do so, we recorded the spiking activity of on average ∼300 well-isolated individual neurons from organotypic cortical cultures. We then constructed weighted, directed networks reflecting the effective connectivity between the neurons. For each neuron, we quantified the amount of computation it performed based on its inputs. We found that rich-club neurons compute ∼160% more information than neurons outside of the rich club. The amount of computation performed in the rich club was proportional to the amount of information propagation by the same neurons. This suggests that in these circuits, information propagation drives computation. In total, our findings indicate that rich-club organization in effective cortical circuits supports not only information propagation but also neural computation. Here we answer the question of whether rich-club organization in functional networks of cortical circuits supports neural computation. To do so, we combined network analysis with information theoretic tools to analyze the spiking activity of hundreds of neurons recorded from organotypic cultures of mouse somatosensory cortex. We found that neurons in rich clubs computed significantly more than neurons outside of rich clubs, suggesting that rich clubs do support computation in cortical circuits. Indeed, the amount of computation that we found in the rich clubs was proportional to the amount of information they propagate, suggesting that in these circuits, information propagation drives computation. The idea that neurons propagate Although there is no agreed upon definition of “computation,” in its simplest form, computation refers to the process of integrating multiple sources of information to produce a new output. This is in contrast to The determinants of strong computation in neural circuits remain poorly understood. Previously, Timme et al.  used theLocal cortical networks, like many complex networks, contain “Thus, here we addressed the critical question: What is the role of the rich club with respect to neural computation? We tested among three possible hypotheses. First, computation is constant throughout the topology of a network: predicting that rich clubs do not perform more or less computation than would be expected by chance. Second, computation grows with increasing information availability: predicting that rich clubs are rich in computation given their high information density. Third, computation decreases with increasing information availability: predicting that rich clubs are computationally poor.To test these hypotheses, we recorded the spiking activity of hundreds of neurons from A→B quantifies how much information is gained about whether neuron B will spike in the next moment obtained by knowing whether A is now spiking, it provides a directional, weighted effective connection. Significant T values  were kept and used to build a graph of the circuit’s functional network. The graph was then used to identify all possible triads in which two transmitting neurons have significant connections to a common receiver neuron. Thus, the same neuron often participated in many triads, the number of which was correlated with the degree of the neuron. Triads were then used to analyze neural computation. Our analysis of neural computation was predicated on the idea that nonlinear integration of multiple inputs implements a form of computation  simultaneously from 25 organotypic cultures of mouse somatosensory cortex. We then quantified the information transfer from each neuron to every other neuron at All TE and synergy values were normalized by the entropy of the receiver neuron in order to cast them in terms of the proportion of the receiver neuron’s capacity that is accounted for by the transmitting neuron, or by computation, respectively. Because of this, all TE and synergy values are in terms of bits per bit. All results are reported as medians with 95% bootstrap confidence intervals  presented in brackets. The three timescales at which TE was computed follow the same pattern of results and are therefore combined for ease of presentation; separate results for each timescale are reported in the Supporting Information . To consider the amount of information that was used in two-input computations, we defined information propagation as the sum of the two inputs  converging on a neuron. Across neurons, the distribution of propagation values was approximately lognormal  indicating that despite finding substantial computation, most information was accounted for by neuron-to-neuron propagation. The variability in computation motivated us to test the hypothesis that the dense interconnectivity of rich clubs serves as a hub, not only for propagation, but also for computation.Computation (measured as synergy), like propagation, varied in a lognormal fashion . The topr) levels  as shown in kth value of r by dividing the sum of all weights for nodes with r ≥ rk by the sum of the n largest weights in the network, where n is the number of edges between neurons with r ≥ rk. The resulting rich-club coefficients approach one when the strongest edges connect the neurons in the subsets defined by r ≥ rk. These rich-club coefficients are then normalized by coefficients from null distributions in order to quantify how much rich clubs differ from those expected by chance .To ensure that the detection of rich clubs was not biased by the spatial sampling of the recording apparatus, we compared the distances between rich-club neurons (defined as the top 30% of neurons in a network) to the distances between all neurons in the network. We found that there were no significant differences between the two distributions of distances  by using multiple approaches. In the first approach, we asked if the mean normalized synergy-per-triad  was significantly greater for triads with receivers inside, versus outside, of a single, representative rich club from each network. The representative rich club for each network was selected at random from among the significant ones. Indeed, we found that mean synergy was 270% greater inside of the rich club . The individual Z-scored synergy values were significant at the α = 0.05 level in 88% (66 of 75) of the networks. The results of these analyses demonstrate that the computation observed in the rich club is not a simple consequence of the magnitude of the TE values that comprise the rich clubs in these networks.A concern that arises when considering whether synergy is stronger inside of rich clubs identified with information theoretic measures, such as TE, is that the rich clubs are defined as having high TE and thus may cause high concentrations of computation for trivial reasons. To test this, we used a spike-time shuffling analysis that preserved TE but disrupted the joint firing statistics between transmitters of a triad. This allowed us to compute the null distribution of synergy that would be expected given the TE that comprised each rich club  suggests that the computation ratio is a relatively stable property of neural information processing in such networks.Seeing that computation and propagation were highly correlated across triads, we asked what range of computation ratios  occurred across networks. As shown in s.r. = −1.58, n = 25 networks, p = 0.11; 0.238 vs. 0.245 at the 1.6–6.4 ms timescale, Zs.r. = −2, n = 25 networks, p = 0.045; and 0.215 vs. 0.224 at the 3.5–14 ms timescale, Zs.r. = 0.97, n = 25 networks, p = 0.33; ρ = −0.36 , Zs.r. = −2.38, n = 25 networks, p = 0.017; ρ = −0.62 , Zs.r. = −3.2, n = 25 networks, p = 0.001; ρ = −0.26 , Zs.r. = −0.98, n = 25 networks, p = 0.33; The implication of a stable computation ratio across triads is that information propagation will reliably be accompanied by computation, thereby accounting for the high density of computation in propagation-dense rich clubs. Because the computation ratio allows computation to be predicted from propagation, it is informative to ask if this ratio varies as a function of rich-club membership. We found that the computation ratio was not substantially different for triads inside, versus outside, of rich clubs .To demonstrate that the result of synergy in the rich club cannot be fully explained by a simple correlation between incoming weight of the receiver and synergy, we asked if there was greater synergy in the rich clubs after the correlation between connection strength and synergy had been regressed out. To do this, we performed a regression between summed incoming connection strength and synergy across triad receivers for a given network and then collected the residual synergy for each triad after accounting for the summed incoming connections. We then asked if the residual synergy values were still significantly greater in the rich club than outside and found that they were .To investigate whether our findings are robust to the method of quantifying computation, we implemented two alternate methods of identifying computation to test if the same results were obtained. In the first, we used an alternate implementation of partial information decomposition (PID). Unlike the standard PID approach, which effectively computes the upper bound on synergy (by assuming maximum redundancy between transmitters), this alternate implementation effectively computes the lower bound of synergy (by assuming no redundancy between transmitters). When using this approach, we find the same pattern of results. That is, mean synergy-per-triad is significantly greater inside versus outside of the rich clubs . As such, use of this classification regime provides an independent, yet related, approach to identifying computation. Consistent with our main results, the concentration of neurons exhibiting nonlinear transfer functions was significantly greater inside versus outside of the rich clubs . Here, we used the same window of time to define the past of the receiver as we do the sender. A concern with this approach, however, is that we may be underestimating the information storage of the neuron with use of short windows. To assess the influence this may have on our results, we repeated our analysis with transmitter spike trains for which the timing of each spike was jittered by a random amount drawn from a uniform distribution with a mean of zero and a width of three times the duration of the past. This disrupts the short-term interactions but preserves the long-term structure, effectively providing a null distribution of values that would be expected given the long-term spiking dynamics alone. By subtracting these values from those obtained from nonjittered spike trains, we were able to assess what effects these values may have had on our findings. We found that after subtracting these residuals, all results held  of the upstream neurons . Here, we defined this window so as to match the window that was used to define the sender state . By doing so, we maintain clear bounds on the timescale at which the functional dynamics were analyzed . A risk of using this window size, rather than a longer size, is that it may underestimate the variance in the receiver spiking that can be accounted for by the prior state of the receiver  and, thus, result in larger propagation or synergy values. To assess the impact this may have had on our results, following the precedent set by others  that matched typical synaptic delays in cortex . Once the data were collected, spikes were sorted using a principal component analysis approach , were used in the construction of the networks. TE values were normalized by the total entropy of the receiving neuron so as to reflect the percentage of the receiver neuron’s capacity that can be accounted for by the transmitting neuron.Networks of TE(J → I) and TE(K → I) with the measured multivariate TE between neurons TE to estimate terms that reflect the unique information carried by each neuron, the redundancy between neurons, and the synergy  between neurons. Redundancy was computed as per Supporting Information Equations S8–S10  and TE(K → I) is greater than TE. The second alternate method identifies neurons that perform the most computation as those with nonlinear input-output transfer functions. The transfer functions are calculated following the methods of Chichilnisky , reported inside of square brackets. Similarly, the median is indicated in figures and the vertical bar reflects the 95% bootstrap confidence limits. Comparisons between conditions or against null models were performed using the nonparametric Wilcoxon signed-rank test, unless specified otherwise. The threshold for significance was set at 0.05, unless indicated otherwise in the text.We thank Olaf Sporns, Randy Beer, and Benjamin Dann for helpful comments and discussion.Samantha P. Faber: Conceptualization; Formal analysis; Investigation; Methodology; Project administration; Software; Validation; Visualization; Writing – original draft; Writing – review & editing. Nicholas M. Timme: Data curation; Formal analysis; Methodology; Resources; Software; Supervision; Writing – review & editing. John M. Beggs: Conceptualization; Data curation; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Writing – review & editing. Ehren L. Newman: Conceptualization; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Supervision; Validation; Visualization; Writing – original draft; Writing – review & editing.http://dx.doi.org/10.13039/100001391), Award ID: 17-12-114. John M. Beggs, National Science Foundation (http://dx.doi.org/10.13039/100000001), Award ID: 1429500. John M. Beggs, National Science Foundation (http://dx.doi.org/10.13039/100000001), Award ID: 1513779. Samantha P. Faber, National Science Foundation (http://dx.doi.org/10.13039/100000001), Award ID: 1735095; Samantha P. Faber, Indiana Space Grant Consortium.Ehren L. Newman, Whitehall Foundation (Click here for additional data file.


Cohabitation has, in a number of countries, become a genuine alternative to marriage. Where this occurs, will we see a convergence in fertility behavior between the two partnership options? We address this question by comparing two societies, Norway and Spain, that contrast sharply not only in the evolution of cohabitation, but also in overall birth rates and public support for families. Using the Generations and Gender Survey for Norway (2007/2008) and the most recent Fertility, Family and Values Survey for Spain (2006), we estimate a three-equation multi-process model for selection into a union and fertility in order to take into account unobserved heterogeneity. For Norway, we find a significant association between selection into either partnership type and fertility, whereas for Spain, a newcomer to cohabitation, we find a significant association between fertility and selection into marriage.The online version of this article (doi:10.1007/s10680-017-9432-6) contains supplementary material, which is available to authorized users. Demographic research has produced no clear evidence as regards the influence of partnership types on fertility. The Second Demographic Transition thesis sees cohabitation as a key marker of postmodern values which stress individualism and self-realization  stability and fertility is inherently ambiguous. We would expect that stable partnerships are more likely to have children. And yet, couples may also have children as a way to shore up a shaky relationship. There is empirical support for both views  and Spain with lowest-low fertility .Our choice of comparison was, however, primarily motivated by clear contrasts in the two countries’ cohabitation and divorce profiles. Norway represents the Scandinavian model where cohabitation has been firmly entrenched for many decades. And Norway exhibits relatively high and stable divorce rates (a crude divorce rate of ca. 2.3).Spain is a newcomer on both counts. And, yet, the pace of change has been truly explosive. Since divorce was legalized in 1981, Spain has moved from the bottom to the top in the divorce league (from a CDR of 0.5 in 1990 to 2.2 in 2010).However, Spanish cohabiters are extraordinarily stable: after 180 months of partnering, the share of intact couples is about twice as large as in Norway  partnerships that tend to be short lived and, on the other hand, more mature and long-lasting arrangements in which childbearing is common  is exogenous, i.e., not correlated with either the level one residual or with the level 2 random effect.Unbiased estimates, however, do not come without a price since we are compelled to make a number of assumptions. Firstly, in each equation we assume that the vector of covariates single to married/cohabiting and those who, after entry into cohabitation, marry the same partner or exit from cohabitation.Our model includes two main components: the first addresses partnership formation and the second fertility transitions. We estimate partnering with two different competing risk models. The first estimates the risk of entering into either cohabitation or marriage for a single woman. The second estimates the risk of marriage with (or separation from) the same partner for cohabiting women. In other words, we take into account both those who change status from Selection into either outcome may be driven by individual characteristics . For instance, those who marry may see marriage as more stable than those who remain cohabiting. The variance–covariance matrix gives us a measure of the correlation between these processes which, in turn, helps us to better interpret these relationships. In modeling partnership dynamics, we take into account repeated events, i.e., those partnerships a woman experiences in life as well as possible partnership ruptures. A woman who experiences a divorce will automatically be assigned the status of singlehood.j enters at each tth month (of episode i), where r1 = 1 is cohabitation and r1 = 2 is marriage. To estimate the first equation, we use a competing risks framework, with hijr1), given the condition that no event has occurred before, can be written as:αr1)(Dijr1)(Tijr2) or ‘separated.’ Thus, adopting the same notation of Eq. , the hazThe second main component of the model focuses on fertility transitions from the date of union formation onwards.This entails that a woman can have her first and second birth with two different partners. In fact, in higher-order relationships, women may self-select into a different type of union compared to women who enter into their first. It has been shown that re-partnered mothers are more likely to opt for cohabitation  2007/2008; for Spain, the Fertility, Family and Values Survey (FFVS) from 2006—the best recent source of data for Spain. Both include retrospective information that allows intergenerational and longitudinal analysis. We include all women in their reproductive years (15–45), censoring at their 45th birthday or at the second birth.parental divorce before the age of 16; country of birth, age at partnership and possible previous partnerships (time varying).A set of dummies for level of education . In both countries, the intermediate category (‘upper secondary’) is the largest. Dummies for birth cohort and current partnership duration (time varying) are included. As to the former, the distribution by birth cohort is fairly homogeneous in both countries.Appendix Tables A1–A4 of the Electronic Supplementary Material present descriptive statistics for the fertility equation sample. Although we focus only on recent cohorts, we present descriptive statistics for older birth cohorts (born 1930–1959) to trace how selection into different types of unions changes over time. In order to properly identify shifts in partnering behavior across the different cohorts, we should have estimated two models for the two periods. However, due to the low number of cohabitants in the old cohorts, multi-process models cannot be identified. We include the standard covariates in the partnering models; the fertility equation, which is our main focus, includes the following covariates:runmlwin command  between entry into cohabitation and subsequently getting married. Similarly, those women who have an above-average risk of getting married have also an above-average risk of exiting cohabitation. This may reflect different unobservable characteristics—for instance, those who get married may experience shorter cohabitation periods. Turning to fertility, we find a positive and slightly significant correlation between entry into marriage and fertility (0.17). Additionally, we find a positive and significant coefficient (0.64) for the interrelation between fertility transitions and entry into marriage (with the same partner) after cohabitation.This suggests that individuals with an above-average risk of getting married have also an above-average risk of childbirth. We find a negative (but not significant) correlation between fertility and entry into cohabitation from the status of single (−0.07). In other words, women who select themselves into cohabitation do not exhibit a stronger childbirth propensity (unless the cohabitation leads to marriage).To summarize: first, entry into parenthood is endogenous with respect to entry into marriage; second, women who are more likely to enter into marriage share unobserved characteristics with those who are more likely to have children. It is important to note that we find no significant negative correlation between entry into cohabitation and childbearing. Women who select themselves into cohabitation are more likely to have children only if that cohabitation precedes a marriage. This is a crucial finding for understanding the Spanish context in terms of childbirth within cohabitation.For Norway, the main diagonal shows statistical significance throughout, implying the presence of individual heterogeneity behind all processes. This underscores the relevance of our modeling approach.The fertility coefficients suggest that women who want children are also more likely to enter into any type of union except marriage. In particular, we find a positive relation between fertility and conception within both cohabitation (0.13) and premarital cohabitation (0.69). Here we observe a major nation–contrast, because Norway exhibits a positive and significant correlation between fertility and entry into cohabitation. This difference may reflect the different degrees of acceptance of childbirth within cohabitation. In other words, Norwegian women do not perceive a non-marital birth as normatively deviant.Moving now to the estimations, our primary interest lies in the coefficient for union type at each birth transition. Tables In both single- and multi-process estimations for Spanish married childless women, the coefficient in the multi-process is smaller. This is because we have ‘cleansed’ the coefficient of the positive correlation between fertility transitions and marriage; without allowing for this correlation, we would have overstated the effect of marriage on childbirth.Turning to second births, the coefficient for married women is negative in both single- and multi-process estimation. Further, the difference in terms of size of the two coefficients is almost zero. This can be explained by the fact that second births in the more recent Spanish cohorts are less common.To sum up, when we examine predicted probabilities for both first- and second-birth transitions in Spain Fig. , marriedTurning to Norway, we see that the coefficient for first births is quite similar in both models (slightly lower in the multi-process estimation). One possible explanation is that first births are common in both types of union, so controlling for time-invariant unobservables makes little difference.Married women at risk of a second birth show a negative coefficient in both the single- and multi-process model. In the latter, the coefficient is smaller than in the single-process estimation. This is partially in line with what we found in the variance covariance matrix. On the one hand, women who are keener to have a child are less likely to get married. On the other hand, those who are more likely to marry their cohabiting partner are also more likely to experience childbirth. Accordingly, in the single-process approach the marriage effect is exaggerated because of selection on unobservables.To sum up, examining the predicted probabilities Fig.  for bothOur starting point was whether cohabitation is increasingly a functional equivalent to formal marriage—at least as far as fertility behavior is concerned. This, we recall, is not what the postmodern ‘less family, more individualism’ version of the Second Demographic Transition thesis would expect Below is the link to the electronic supplementary material.


These findings indicate potentially overlapped pathogenic mechanisms in these two diseases, which may help uncover new therapeutic targets to ameliorate disease progression.Rheumatoid arthritis (RA) and osteoarthritis (OA) are common rheumatic disorders that primarily involve joints. The inflammation of the synovium can be observed in both of the two diseases. Synovial fibroblasts (SFs) play an important role in the inflammatory process of the synovium. The functional states of synovial fibroblasts are heterogeneous, and the detailed transition process of their functional states is still unclear. By using transcriptomic data of SFs at a single-cell level, we found a similar transition process for SFs in RA and OA. We also identified the potential regulatory effects of the WNT signaling pathway, the TGF- Rheumatoid arthritis (RA) and osteoarthritis (OA) are common rheumatic disorders that primarily involve joints. RA is an autoimmune disease, and an immune-mediated etiology associated with stromal tissue dysregulation can together propagate chronic inflammation and articular destruction . OA has http://www.ncbi.nlm.nih.gov/geo/). From a total of 384 SFs, 192 SFs were obtained from OA patients, while the other 192 SFs were obtained from RA patients. Expression levels of mRNA in this dataset were assayed with the Smart-Seq2 protocol .–19.εRI spathway) . Interesβ signaling pathway and the term cell cycle). For RA SFs, the FcεRI signaling pathway, the ERBB signaling pathway, the calcium signaling pathway, the VEGF signaling pathway, the chemokine signaling pathway, and the cytokine-cytokine receptor interaction were enriched in state 5, while for OA SFs, only the FcεRI signaling pathway was enriched in state 5  to activated states with different functional patterns . The elevated expression level of PDPN can be observed after stimulation with TNFt manner . The lowot ICAM1 , 21–23. ot ICAM1 , 25. Theammation . All the state 2 .β signaling pathway along the transition branch from state 4 to state 2 or 1 in RA indicated the potentially high TGF-β level in the surrounding environments of these SFs , which may verify the results that CD34-THY1+ SFs might be important subsets with pathological behavior in rheumatoid arthritis . Howeverhese SFs . TGF-β c of MSCs . Thus, odiseases , 32. ThuThere are still some limitations in our study. Although the scRNA-seq data of 345 SFs were used in this analysis, they came from only 4 patients, which may lead to results biased by the individual characteristics of the limited number of patients. Also, the detailed effects of the pathways previously described need to be verified.β signaling pathway, the FcεRI signaling pathway, and the ERBB signaling pathway on the transition of synovial fibroblasts in both RA and OA, which may provide potential therapeutic targets to both conditions.In conclusion, our study revealed the similar transition processes of SFs in both RA and OA, described the corresponding changes of the functional states in the transition process, and indicated the potential regulatory effects of the WNT signaling pathway, the TGF-


Human T cell leukemia virus type 1 (HTLV-1) was the first discovered human retrovirus and the etiologic agent of adult T-cell leukemia and HTLV-1-associated myelopathy/tropical spastic paraparesis. Shortly after the discovery of HTLV-1, human T-cell leukemia virus type 2 (HTLV-2) was isolated from a patient with hairy cell leukemia. Despite possession of similar structural features to HTLV-1, HTLV-2 has not been definitively associated with lymphoproliferative disease. Since their discovery, studies have been performed with the goal of highlighting the differences between HTLV-1 and HTLV-2. A better understanding of these differences will shed light on the specific pathogenic mechanisms of HTLV-1 and lead to novel therapeutic targets. This review will compare and contrast the two oldest human retroviruses with regards to epidemiology, genomic structure, gene products, and pathobiology. In 1980, Poiesz et al. reported the discovery of the first human retrovirus isolated from a patient with cutaneous T-cell lymphoma. This virus is now known as human T-cell leukemia virus type-1 (HTLV-1) , while HHTLV-1 is associated with several diseases, including adult T-cell leukemia (ATL) and HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP) –7. InterMany studies over the years have dissected differences between HTLV-1 and HTLV-2. Recent years have focused on differences between the regulatory protein Tax and the antisense-derived proteins, HBZ (HTLV-1) and APH-2 (HTLV-2). The different cellular pathways and signaling cascades that these proteins activate likely play a key role in the divergent pathogenic outcomes of these viruses. Studies of HTLV-1 are of high importance due to the diseases associated with the virus. An increase in studies of HTLV-2 would be beneficial to learn what this virus lacks causing it to not be associated with disease. This review will compare and contrast the two oldest human retroviruses and emphasize the differences that exist between these viruses and the potential they may have for treatment of HTLV-1-associated diseases.There are an estimated five to ten million individuals infected with HTLV-1 worldwide with endemic regions of infection in Southwest Japan, sub-Saharan Africa, South America, the Caribbean, and regions of the Middle East and Australo-Melanesia . The estSeroprevalence of HTLV-1 in areas of endemicity is estimated at 1–2%, and was found to reach as high as 20–40% in individuals greater than 50 years of age . A majorHTLV-1 demonstrates robust genetic stability. Mapping of stable nucleotide substitutions specific to varied geographic regions has been used to classify virus strains into geographic subtypes , 17. TheWith an estimated 800,000 infected individuals worldwide, HTLV-2 is far less prevalent than HTLV-1. Most documented HTLV-2 infected individuals are found in the United States  highly concentrated in the Native American and intravenous drug user populations. A similar epidemiologic pattern is found in the second most HTLV-2 infected region, Brazil . The lower prevalence of HTLV-2 when compared to HTLV-1 reflects specific concentration of infection within Native American groups and intravenous drug users . HTLV-2 HTLV-1 and HTLV-2 require cell-to-cell contact for efficient transmission . Both viThere are three primary modes of HTLV transmission: vertical (e.g. during parturition or breast feeding), parenteral , and sexual –32. BreaEnv. Both HTLVs encode an antisense gene, HBZ for HTLV-1 and APH-2 for HTLV-2, located on the negative or minus strand of the proviral genome.HTLV is a member of the delta retrovirus family. These viruses are complex retroviruses that express regulatory and accessory genes, in addition to the structural and enzymatic genes common to all retroviruses. The proviral genomes of HTLV-1 and HTLV-2 are depicted in Fig. After integration of the proviral genome, several different HTLV transcripts will be produced  that Tax-2 lacks. It has been shown that this PBM is important for PI3K/AKT/mTOR pathway activation via attenuation of negative regulators PTEN and PHLPP through competitive binding of DLG-1 . The PI3Tax-1 and Tax-2 have been shown to drive various cellular pathways via activation of MAPKs. Tax has been documented to bind MEKK1, TAK1, and GPS2 which, in turn, play roles in activation of the NF-κB and JNK pathways , 86.Lastly, Tax-1 has been shown to repress the activity of the critical tumor suppressor gene p53 through various pathways including the NF-κB and ATF/CREB pathways discussed above . Tax-2 hHTLV-1 and HTLV-2, both encode gene products from the antisense strand of the proviral genome, termed HBZ and APH-2, respectively. Like Tax-1 and Tax-2, HBZ and APH-2 feature multiple similarities and differences that likely contribute to the pathogenic potential or lack thereof. The prominent similarities and differences will be discussed in this section and are summarized in Fig. HBZ and APH-2 mRNAs are transcribed from the 3′ LTR and are polyadenylated [The presence of the HTLV-1 antisense transcript HBZ was clearly demonstrated by Gaudray et al. in 2002 after prior identification of a conserved open reading frame in the antisense strand of the HTLV-1 genome , 91. Yeaenylated . HBZ is HBZ protein represses Tax-mediated proviral transcription through heterodimer formation with CREB, CREB-2, CREM, and ATF-1 , 93–95. Deletion of either antisense protein from their respective HTLV molecular clones has no effect on in vitro immortalization of primary T-lymphocytes. However, antisense protein deletion does result in divergent phenotypes in vivo using a rabbit model of infection. Loss of HBZ lowers the replication and persistence of HTLV-1 infection while loss of APH-2 increased in vivo HTLV-2 replication and proviral load in rabbits . Thus, ASeveral other functions have been attributed to HBZ. These include induction of genomic instability through double strand breaks , enhanceRex-1/Rex-2, p21Rex/truncated Rex, p30/p28, and p12/p10. HTLV-1 also expresses p13 and p8 while HTLV-2 expresses p11, these three proteins do not have a homologue in the opposing virus. This section will briefly touch on the remaining gene products of HTLV.HTLV-1 and HTLV-2 express other regulatory and accessory genes including The main function of Rex in the viral lifecycle is to promote the export of the full length unspliced mRNA from the nucleus . This isHTLV-1 expresses one isoform of Rex known as p21Rex, while HTLV-2 expresses several isoforms known as truncated Rex (tRex). HTLV-2 tRex is expressed from two different mRNAs and via different initiation codons resulting in four distinct isoforms between the sizes of 17 and 22 kDa . Both p2Tax/Rex mRNA in the nucleus resulting in inhibition of virus production [p30 and p28, expressed by HTLV-1 and HTLV-2 respectively, each function to retain the spliced oduction , 112. p2oduction . Interesoduction . p30 inhoduction . HTLV-1 oduction , 117. FeThe last gene products with similar sequence and function between the two viruses are HTLV-1 p12 and HTLV-2 p10. p12 is a membrane bound protein that is localized to the endoplasmic reticulum (ER) and Golgi. p12 appears to play a role in dendritic cell infection, but deletion of p12 from the provirus does not alter PBMC immortalization in vitro or viral persistence in vivo . p12 redHTLV-1 p13 is a mitochondrial-associated protein of 87 amino acids, which is identical to the carboxyl-terminal 87 amino acids of p30 . Mutatiop11 is a unique protein expressed by HTLV-2. p11 is expressed from the same mRNA transcript as p10. p11 has been shown to bind to MHC-1 potentially modulating the immune response .+ T-lymphocytes, and HTLV-2 in CD8+ T-lymphocytes [+ T-cells demonstrate high levels of HSPG expression and minimal GLUT1, whereas CD8+ T-cells demonstrate the opposite. A recent in vivo study found that the tropism for CD4+ and CD8+ T-lymphocytes was equivocal 1-week post-inoculation of New Zealand White rabbits with HTLV-1 and HTLV-2 [+:HTLV-1 and CD8+:HTLV-2 tropisms were established several weeks after infection [The in vivo tropism of HTLV-1 and HTLV-2 differ, with HTLV-1 being primarily detected in CD4phocytes , 125. Prphocytes , 127. GLInfection with either HTLV-1 or HTLV-2 have been shown to result in clonal proliferation of T-cells , 129. AnHTLV-1 and HTLV-2 are highly related viruses with different pathobiology. While being closely related with sequence and genomic structure, there exists several differences between HTLV-1 and HTLV-2. Several studies within the field have suggested these differences may help explain the different disease outcome between these two viruses. It is worth noting that the smaller populations of individuals infected with HTLV-2 may mask a potential disease caused by this virus, but in vivo and in vitro work by members of the HTLV research community clearly demonstrate the lower transforming capacity of HTLV-2. The regulatory Tax proteins and antisense-derived proteins of the two viruses are the most well compared of HTLV-1 and HTLV-2.The few differences that exist between HTLV-1 and HTLV-2 require further intense study. The complete exploration of what makes HTLV-1 pathogenic compared to HTLV-2 would open many avenues to fight this pathogenic capability and improve the livelihoods of individuals infected with HTLV-1. Also, increased understanding of how HTLV-1 causes cancer has broad impact on the cancer field as a whole, potentially uncovering new therapies for other cancer types.


Objective: Population and its corresponding problems are among multidimensional and complicated issues of human communities and their related features are the basis for making any plan or policy. Fertility, as one of the principle components of population growth, is an issue that has always been taken into consideration and extensive research has been carried out to recognize factors affecting on it. Therefore, the authors decided to study the most important factors influencing fertility rate in Iran by conducting a longitudinal study and considering the effect of various time periods on its population changes. Materials and methods: This is a descriptive-analytic study. Its required information is a combination of cross-sectional and time series data (panel data) that were extracted from 1966 to 2013 from Iran’s population categorized by the country’s 24 provinces and from statistical yearbooks of Statistical Center of Iran and Organization of Civil Registration. The final estimations were made using Eviews 7 and STATA 12 software. Findings showed that variables of marriage, women’s level of education, unemployment, population policies, Sunni population, economic policies and annual expenses of households have influenced the fertility rate.Results: Based on the research results, marriage and women’s level of education respectively had the most positive and the most negative effects on the fertility rate. Then, unemployment, family planning policies, policies of paying cash subsidies and total annual household expenses had reverse effects on the fertility rate and the policies of paying cash subsidies and Sunni population had positive effects on the fertility rate.Conclusion: In order to make policies of increasing fertility rate effective by governmental and politicians’ planning, more attention should be paid to providing conditions for marriage and reducing unemployment. Population and its corresponding problems are among multidimensional and complicated issues of human communities and their related features are the basis for making any plan or policy. In fact, population is one of the important economic and social components in any community and population growth (fertility status) should be under control in order to reach sustainable development .The phenomenon of fertility is one of the important natural events of population and one of the important elements of population growth, for the increase of which, some countries apply incentive policies and some others apply punitive ones. Certainty and stability in population issues do not have many applications and no specific reason can be used to determine their dimensions. On the other hand, there is not a fixed and permanent relation between their variables .Recognition of fertility dynamics and factors influencing it, which form the most important population component in today’s world, are inevitable necessities in development programs. This is particularly of high importance for developing countries that are more concerned about development and growth. As a developing country, Iran has faced a rapid reduction in fertility during the last decade .Although the common attitude is that reduction of fertility in recent years is a result of economic pressures and after overcoming the economic problems, fertility can be expected to increase again but factors such as urbanization, marriage age, Improve in education especially in women, public family planning policies and world culture will definitely lead to a more reduction of fertility in the upcoming decade and it is expected that if families enjoy a better economic condition, they will care more about the quality of their children and will not think about the number of them .Based on the census done in 2006, the amount of fertility throughout the country was 1.8 children per mother and country’s population growth was 1.62 and in the census done in 2011, the average of country’s population growth was announced to be 1.29 . While tFertility, as one of the major components of population growth is an issue that has always been the center of attention and extensive research has been carried out in the field of recognizing the factors influencing it in Iran and in foreign countries . ExampleThe present study is different from other studies of the same type in some aspects which include the use of Panel approach and the study of the issue in a macro view by the use of general information about provinces, not the families separately, as well as the use of questionnaires. Unlike being abundant in studies carried out in other countries, this type of research has had no precedence in Iran to the best knowledge of researchers. According to the aforementioned issues, the most important factors influencing the rate of fertility in Iran were decided to be investigated by a study that could be carried out over time and by considering different periods of population changes.The present paper is a socioeconomic study based on a descriptive-analytical model. The required information to carry out the study was a combination of cross-sectional and time series data (panel data) that were extracted from 1966 to 2013 from all residents of country differentiated by 24 provinces and from statistical yearbooks of Statistical Center of Iran and the country’s Civil Registration Organization. As the number of Iran provinces was changed during periods, researchers had to use the least number at the beginning of the period and integrated data for divided provinces in other years. Panel data is one of the approaches of econometrics and is a combination of cross-sectional and time series data. The limitations that exist in each one of the time series models (autocorrelation) and cross-sectional data (heteroskedasticity) can be reduced in a panel model. By combining these two groups in a panel, and with the increase of the number of observations and the degree of freedom, the alignment problem between explanatory variables will decrease and the efficiency of econometric estimation will increase .In the present study, fertility rate (FR) as a dependent variable [Total fertility rate = Σ ] has been analyzed against four groups of descriptive variables. The first group, economic indexes of provinces include variables that describe the economic status of the provinces namely unemployment rate (UnempR) and the family’s total annual expenses (FaTExp). The second group constitutes the economic policies of the government which include cash and non-cash subsidy policies (Sub). It’s expected that paying subsidy lead to more fertility because of Motivational effect in economic aspect. The third group includes the population policies of the government which are the family planning policies (FaPlan). The fourth group, socio-economic indexes of provinces, including marriage rate (MarR), women’s education rate (EduWomR) and the ratio of Sunni population to the whole population in the province (SunR), It is thought, Sunni population has cultural and religious specificities that lead to more fertility so more ratio of this group in provinces population may have direct relation with fertility rate . It should be mentioned that in specification process many other variables were studied and were deleted from the model base on goodness of fit test. For example women employment, men education, Finally the applied multiple linear regression model was as follows:FRit=αi+β1MarRit+β2EduWomRit+β3UnempRit+β4FaPlanit+β5SunRit+β6Subit+β7FaTExpit+εitIn this regression, “i” stands for provinces and “t” shows the years. Also β coefficient of each variable indicates its level of effect related to that dependent variable and α coefficient is the intercept of the model.αi is an intercept which is random. In linear regression, distribution of error term is considered normal. As in “basic econometrics” book written by Damodar Gujarati it’s mentioned, this consideration has many benefits. “u is frequently assumed to follow a normal distribution, there is no theoretical reason for the selection of this or other distributional forms for u” (s for u”  19)..αi is a1: not paying the subsidy, D2: paying non-cash subsidy (ten coupons), D3: paying non-cash subsidy (five coupons), D4: paying non-cash subsidy (four coupons), D5: paying non-cash subsidy (three coupons) and D6: paying cash subsidy.Programs and policies of paying cash and non-cash subsidy and its absence have been divided into six periods in dummy variable forms. D1: presence of family planning policies and D2: absence of public family planning policies for population reduction. Family planning policies were analyzed during two periods in the form of dummy variables. D1: provinces with less than five percent of Sunni population, D2: provinces with Sunni population of five to fifty percent and D3: provinces with more than fifty percent of Sunni population.Sunni population has also been divided into three categories of dummy variables: D0 = Pooled, H1 = Fix Effects) and Breusch-Pagan Test  were used to determine the type of model. Hausman Test  was used to decide between fixed effects and random effects models and when the type of the model was determined, the final estimation was done by Eviews 7 and STATA 12.Finally, by the use of related tests, the appropriate estimation method  was selected. First Chow Test  was applied and the number of coupons were high was positive which means they had a direct effect on fertility rate. However, the last two periods during which the policy of paying non-cash subsidy had reached its lowest level (coupons for three items) and the policy of paying cash subsidy was applied, had negative effect coefficients and a reverse effect on fertility rate.Based on the results of the model of economic indexes, effect coefficient of family’s total annual expenses on fertility rate was lower than the coefficient of all other variables. In order to ensure the obtained results, the index of family’s total annual expenses was divided into annual food and non-food expenses of a family and the effect of non-food expenses of a family that was a representative of expenses such as rental of a house, transportation and peripheral expenses such as taking care of children were studied. Results showed that these expenses also have negative but little effect on fertility rate over time. In the next step, family’s annual non-food expenses were divided into urban and rural aspects. After estimating the model, the coefficient of this model turned out to be negative for both urban and rural households that showed the reverse but small effect of expenses on fertility rate.In this study, attempts were made to make use of appropriate models to evaluate the collected data. However, the present study has some limitations. There might be other variables that can affect fertility rate and have not been considered in this study due to the absence of some other data, instances of which may be variables like life expectancy, health indexes, singleness and the ratio of ethnic minorities. In addition, inaccessibility to the data that were influential in fertility rate and inaccessibility to the required data regarding the households were some of the limitations in the present study. On the other hand, because data resources did not overlap or were not consistent with each other, the obtained results might have been influenced. Finally, the present research estimated and analyzed different models, which is unprecedented.Based on the obtained results, marriage has been the main and most important factor influencing fertility rate. Other studies confirm the results of this research like the study conducted by Iman et al.  which shFindings of studies of Hondroyiannis  and JafaWith the improvement of women’s level of education and their entering the society, marriage age has increased and their inclination to have children has decreased and on the other hand, information and accessibility to tools for fertility control and pregnancy prevention has increased. Also better job opportunities will make women feel independent economically, socially and mentally. Educated women emphasize the quality of children more than their quantity. Therefore, they will face less fertility. According to numerous studies such as Rahnavard et al. , AkaberiUnemployment rate is one of the most important economic causes of fertility reduction. Results of other studies confirmed this fact. Seemingly, it was shown in the studies of Kreyenfeld , Adsera During the years when family planning policies were implemented, these policies were effective and fertility rate has reduced. Research findings of Kalantari et al.  27) ind ind27) iVarious religious minorities have different attitudes about fertility. Having more Sunni population has had positive effects on fertility rate. Findings of studies done by Mahmoodian and Nobakht , HashemiAt the time when cash subsidy policy was implemented, unlike the theory that paying cash subsidy must encourage people to higher levels of fertility, coefficient of the period of policy of paying cash subsidy had become negative due to other reasons such as an increase in unemployment resulted from paying cash subsidy, ineffective allocation of them or factors that have influenced the level of fertility over time. Interpreting these results, one can say that the power of negative effect of variables such as unemployment and women’s education rate in the society has been so high that has superseded the positive effect of paying cash subsidy on fertility rate during the period. Mention to educated women attitudes about fertility importance and preparing good condition and supportive environment for parents can be so helpful. Also, paying cash subsidy has temporarily reduced the financial load of more children and has not been considered a helpful fundamental policy in the long run. Research results of Kalwij  also indUnlike the public’s belief that one of the most important factors of reducing fertility rate is increasing expenses and income status of households, one can see that the negative index of family’s total annual expenses has not had any remarkable effect on the reduction of fertility. Other studies are also consistent with the results of this research about negative sign of this variable. For example, Heydari-Sooreshjani et al.  and HezaIn order to make policies of increasing fertility rate effective by governmental and politicians’ planning, more attention should be paid to providing conditions for marriage and reducing unemployment. Getting married and starting a family can be possible in a society if unemployment is reduced through creating jobs, especially for men, providing accommodations, increasing public awareness and scientific justification of marriage and fertility logic because as long as the youth are unemployed and have no income, that is until they live in an insecure economic condition, they cannot think about marriage and delay it. Consequently, childbearing will be postponed, too.


Paroxysmal atrial fibrillation (AF) combined with obstructive sleep apnea hypopnea syndrome (OSAHS) is very common in clinical practice. Traditional Chinese medicine (TCM) rule of regulating the liver based on psycho-cardiology shows satisfactory effectiveness in the treatment of paroxysmal AF combined with OSAHS. However, its underlying pharmacological mechanism has not yet been elucidated. This study applied network pharmacology to identify 94 active components in the six TCM liver-regulating herbs and 182 corresponding targets from several databases and comprehensive literature studies, as well as retrieved AF combined with OSAHS-related targets. Cytoscape software was adopted to construct the component-component target network and component-putative target-AF combined with OSAHS target network. Then, we obtained 38 putative therapeutic targets against AF combined with OSAHS. After the production of a putative therapeutic target interaction network, topological analysis was adopted to determine the core targets of TCM liver-regulating herbs in the treatment of paroxysmal AF combined with OSAHS. For all putative therapeutic targets, biological process analysis and pathway enrichment analysis were utilized to investigate the possible mechanism of TCM liver-regulating herbs in the treatment of paroxysmal AF combined with OSAHS. Mechanistically, it included positive regulation of nitric oxide biosynthetic process, aging, response to hypoxia, TNF signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, neuroactive ligand-receptor interaction, and calcium signaling pathway. Especially, six core targets of TCM liver-regulating herbs, namely, TNF, STAT3, AKT1, IL-6, TP53, and INS, were significant in the regulation of the above biological processes and pathways. This study demonstrates the multicomponent, multitarget, and multipathway feature of TCM liver-regulating herbs, provides an extensional foundation for further research, and facilitates the reasonable application of TCM liver-regulating herbs in treating paroxysmal AF combined with OSAHS. Atrial fibrillation (AF) is one of the most common types of arrhythmia during clinical practice and is associated with elevated cardiovascular morbidity and mortality rate . ObstrucTCM characteristic of AF patients with OSAHS who frequently showed irritability, anxiety, and depression is more likely complicated with qi depression and stagnation . TCM rulAdditionally, herbal formulae possess the advantages of simplicity, convenience, efficiency, and economy. TCM syndrome differentiation and treatment conforms to the concept of individualized therapy in modern medicine. Herbal formulae can exert its therapeutic effect through acting on multiple targets and multiple pathways, so it is difficult to elucidate the mechanisms of action through conventional research . Fortunahttp://lsp.nwu.edu.cn/tcmsp.php, updated on May. 31, 2014) database and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM) platform (http://bionet.ncpsb.org/batman-tcm/). TCMSP database is the largest pharmacological data platforms for TCM. They encompass many herbs, chemical components, and pharmacokinetic properties, which include absorption, distribution, metabolism, and excretion (ADME) information in the Pharmacopoeia of the People's Republic of China (2010 edition). Owing to the disadvantages of biological experiments as being time-consuming and expensive, identification of ADME  characteristic has now become an acknowledged model in pharmaceutical research. In this study, two important ADME parameters including bioavailability (OB) and drug-likeness (DL) were utilized to screen bioactive components. The screening criteria are OB ≥ 30% and DL ≥ 0.18 i-oscillation frequency and prevented cardiac remodeling [α, IL-1β, IL-6, and IL-18 and suppression of activation of NF-κB and AKT [In the component-component target network, quercetin, kaempferol, and sitosterol were recognized as significant active components. Quercetin and kaempferol account for most of the putative targets from six TCM liver-regulating herbs, suggesting that the two active components play critical role in pharmacological mechanism of TCM liver-regulating herbs. Quercetin was shown to be associated with a variety of AF combined with OSAHS targets, including TNF, IL-6, SCN5A, NOS2, NOS3, and PPARG. Several reports have demonstrated that quercetin possesses antioxidative, anti-inflammatory activities, antiproliferative activities, and free radical-scavenging , 31. It nd GATA4 . Early rmodeling . The invmodeling . Additio and AKT . The pro and AKT .In the AF combined with the OSAHS target network, INS, IL6, and TNF are selected as the hub nodes. Insulin resistance induces both atrial structural remodeling and abnormal intracellular calcium homeostasis, contributing to increased AF susceptibility . It is r2+ level and arrhythmogenesis in cardiomyocytes [In the component-putative therapeutic target-pathway network, 38 therapeutic targets were primarily modulated by quercetin, luteolin, kaempferol, apigenin, stigmasterol, isocorypalmine, and hyndarin. The 6 core targets were determined by network topology analysis, including TNF, STAT3, AKT1, IL-6, TP53, and INS. Various inflammatory cytokines regulate the function of ion channels and calcium homeostasis. TNF induces abnormal Camyocytes . TNF canmyocytes . Furthermyocytes . These smyocytes . It is rmyocytes . Targetimyocytes . For STAmyocytes . For AKTmyocytes . TP53, wmyocytes . For INSmyocytes . Insulinα and IL-6 [+ channel expression and downregulation of Ca2+ channel expression in OSAHS experimental models contribute to shortening of AERP and increase in AF susceptibility [In this study, we performed enrichment analysis to clarify the multiple mechanisms of TCM liver-regulating herbs against AF combined with OSAHS from a holistic and systematic perspective. In the GO enrichment analysis, the targets were closely related to positive regulation of nitric oxide biosynthetic process, aging, response to hypoxia, and positive regulation of ERK1 and ERK2 cascade. The results suggested that TCM liver-regulating herbs may exert therapeutic effect through acting on these biological processes. In the KEGG pathway enrichment analysis, we obtained that the pathways mainly associated with AF combined with OSAHS were TNF signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, neuroactive ligand-receptor interaction, and calcium signaling pathway. It is shown that oxidative stress and inflammation associated with OSAHS have been implicated in AF initiation and perpetuation . Elevateand IL-6 . The uprtibility . Recurretibility , 57. TheIn the present study, we identified 94 active components of six TCM liver-regulating herbs and 182 component targets, showing the characteristic of multicomponent and multitarget of herbs. The herbs exerted therapeutic effects on AF combined with OSAHS by acting on 38 targets, which were primarily hit by quercetin, luteolin, kaempferol, apigenin, stigmasterol, isocorypalmine, and hyndarin. Additionally, 6 core targets were identified by network topology analysis, namely, TNF, STAT3, AKT1, IL6, TP53, and INS. The GO enrichment analysis demonstrated that the therapeutic targets of herbs in the treatment of AF combined with OSAHS might be tightly associated with biological processes, for instance, positive regulation of nitric oxide biosynthetic process, aging, response to hypoxia, positive regulation of ERK1 and ERK2 cascade, positive regulation of vasodilation, and positive regulation of transcription from RNA polymerase II promoter. Moreover, the KEGG pathway enrichment analysis indicated that the action target of herbs might be closely related with multiple signaling pathway, including TNF signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and calcium signaling pathway. These pathways play significant role in therapeutic effects of TCM liver-regulating herbs in the treatment of AF combined with OSAHS.In summary, the present study systemically analyzed the complicate correlation among multiple components, targets, and pathways for TCM liver-regulating herbs in the treatment of AF combined with OSAHS. The results explored the pharmacological and molecular mechanisms of TCM liver-regulating herbs acting on paroxysmal AF combined with OSAHS, which may lay a good theoretical foundation for further experimental verification and facilitate the widespread application of TCM liver-regulating herbs in treating arrhythmia. However, further experimental research is urgently needed to verify the prediction.