Mitogen-Activated Protein Kinase (MAPK) cascades are conserved signaling modules that integrate multiple signaling pathways. One level of control on the activity of MAPKs is through their negative regulators, MAPK phosphatases (MKPs). Therefore, MKPs also play an integrative role for plants responding to diverse environmental stimulus; but the mechanism(s) by which these phosphatases contribute to specific signals remains largely unknown. In this review, we summarize recent advances in characterizing the biological functions of a sub-class of MKPs, dual-specificity phosphatases (DSPs), ranging from controlling plant growth and development to modulating stress adaptation. We also discuss putative regulatory mechanisms of DSP-type MKPs, which plants may use to control the correct level of responses at the right place and time. We highlight insights into potential regulation of cross-talk between different signaling pathways, facilitating the development of strategies for targeting such cross-talk and to help improve plant resistance against adverse environmental conditions without affecting the growth and development. To rapidly adapt to various environmental challenges, plants need to balance diverse signal inputs which involves crosstalk between different signaling pathways. A common strategy for integrating these signals is through use of shared components, including mitogen-activated protein kinase (MAPK) cascades that play essential roles in signal transduction and amplification for many distinct cellular responses. MAPK cascade modules are conserved in all eukaryotes and consist of three kinase components: MAPK kinase kinases (MAPKKKs) phosphorylate dual-specificity MAPK kinases (MAPKKs), which then phosphorylate and activate the terminal MAPKs in a Thr-X-Tyr activation loop  and metal-dependent protein phosphatases (PPMs), which are serine/threonine phosphatases, and tyrosine phosphatases (PTPs) Shi, . RepresePTPs are biochemically distinct protein phosphatases and include tyrosine specific phosphatases and dual-specificity (Ser/Thr and Tyr) phosphatases (DSPs)  phosphatases (DSPs) belong to a subfamily of the tyrosine phosphatases (PTPs) that can dephosphorylate both phosphoserine/phosphothreonine and phosphotyrosine within the activation loop of MAPKs , synthetic auxins and auxin transport inhibitors  and PDR9 genes were characterized, and these two genes encode ABC transporters implicated in the efflux of synthetic auxins  mutants, which display a defect in a microtubule-associated protein  in the putative kinase interaction motif (KIM) of MAPKs such that the mutation might interfere with interactions with the target MAPK(s). Therefore, it has been proposed that PHS1 may regulate multiple MAPKs; and a subset of its target kinases may be involved in the organization of cortical microtubules. To further investigate the mechanism underlying microtubule regulation, a screen for PHS1-interacting MAPKs was performed; and MPK12 and MPK18 were identified by yeast two-hybrid assays  was expressed in the background of phs1-5 to examine if the phosphatase-dead form of PHS1 functions as a dominant-negative microtubule destabilizer  which acts in the apical meristem to induce floral identity genes  treatment, including activation of MPK6 and MPK3, production of reactive oxygen species (ROS), accumulation of a subset of PAMP-regulated transcripts, and inhibition of seedling growth  DC3000 (hereafter referred to as DC3000)  dephosphorylates phospho-MPK3 and phospho-MPK6 ibr5-7 suppresses the chilling-induced defense responses of chs3-1  to stabilize CHS3 protein, thus increasing the accumulation of CHS3 . IBR5 interacts with and promotes the accumulation of SNC1  and DC3000 (avrRps4)  proteins. IBR5 plays a positive role in regulating R protein CHS3, as evidenced by that mutation of mkp1 mutant results in hypersensitivity to various genotoxic stresses , suggesting that MKP1 plays essential roles in genotoxic stress relief -induced nitric oxide (NO) production in guard cells , superoxide anion O2− and hydrogen peroxide levels in the TMKP1 transgenic seedlings  and downregulation of two ABA-repressed genes  , including hydrogen peroxide (H2O2), hydroxyl radical (HO.), singlet oxygen (1O2) and superoxide anion (mkp2 mutants was more severely inhibited by the oxidative agent methyl-viologen (MV) compared to wild type plants , mkp1 mutants produced more ROS than in wild type plants  are generated from partial reduction of oxygen  treatments , contributing to differences in amplitude and duration of signaling. Many examples have shown that the phosphatase activity of MKPs can be regulated by post-translational modification. Mammalian MKP1s (not an orthologue of plant MKP1s) and yeast Msg5 are phosphorylated by their own substrates MAPKs, and phosphorylation regulates not only the activities but also the abundance of the phosphatases, establishing an efficient negative feedback loop ; and phosphorylation of TMKP1 is required for the interaction , which was mainly localized in cytoplasm, the localization of both MAPKs also changed to the cytoplasm   substrates but decreases phosphatase activity on the phosphotyrosine of myelin basic protein (MBP), suggesting that calmodulin differentially regulates substrate specificity  but not CaMBDII mutant (W678R) can be activated by CaM, which indicates that CaMBDII plays a more important role than CaMBDI for the regulation of MKP1  binding proteins, where CaM is a CaThis review summarizes current knowledge of the roles of MKPs in multiple signaling pathways. MKPs are involved in many aspects of a plant's life cycle, including growth and development as well as the adaption to various biotic and abiotic stresses. As different signaling pathways integrate through MKPs, it is critical for MKPs to undergo precise regulation to generate correct biological outcomes. These investigations of regulatory mechanisms have provided insights into putative mechanisms that might explain how the phosphatases assist in producing specific signals. The potential combinatorial complexity of different transcriptional/post-transcriptional regulations, differential localization affecting subcellular pools of MAPKs, and the possibility to integrate information from other pathways may have profound effects on organizing the amplitude and duration of targeted kinases.As important as the MKPs appear to be, most of our knowledge regarding their functions is limited to their roles in negatively regulating MAPK signaling, and few other potential upstream and/or downstream targets have yet to be characterized. Genome-wide analyses will certainly facilitate a better understanding of MKPs-mediated signaling pathways by identification of both molecular players in the pathways as well as additional putative MKP targets. A better understanding of how plants coordinate and balance different signaling pathways in response to diverse environmental stimuli could lead to more rationally designed strategies for improving crop yield under changing environmental conditions. Promising results such as the deletion of MKP1 resulting in enhanced resistance to various biotic and abiotic stresses without compromising plant growth (Ulm et al., LJ and SP conceived the main subject of this review and wrote the manuscript. YC and LL provided the suggestions and revisions.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.


In the healthy endometrium, progesterone and estrogen signaling coordinate in a tightly regulated, dynamic interplay to drive a normal menstrual cycle and promote an embryo-receptive state to allow implantation during the window of receptivity. It is well-established that progesterone and estrogen act primarily through their cognate receptors to set off cascades of signaling pathways and enact large-scale gene expression programs. In endometriosis, when endometrial tissue grows outside the uterine cavity, progesterone and estrogen signaling are disrupted, commonly resulting in progesterone resistance and estrogen dominance. This hormone imbalance leads to heightened inflammation and may also increase the pelvic pain of the disease and decrease endometrial receptivity to embryo implantation. This review focuses on the molecular mechanisms governing progesterone and estrogen signaling supporting endometrial function and how they become dysregulated in endometriosis. Understanding how these mechanisms contribute to the pelvic pain and infertility associated with endometriosis will open new avenues of targeted medical therapies to give relief to the millions of women suffering its effects. The endometrium is a complex and dynamic tissue composed of epithelial cells, both luminal and glandular, surrounded by supporting stromal cells, together comprising the innermost layer of the uterus. The primary function of the uterus is supporting fertility, and the endometrium is the layer critically involved in receiving an embryo, facilitating implantation and decidualization, and supporting embryo growth and development until placentation. Successful pregnancy establishment requires an endometrium that is receptive to blastocyst invasion and ready to undergo decidualization, which is dependent upon hormonally regulated molecular processes that allow pregnancy establishment during the period of the menstrual cycle known as the window of receptivity ,2. The pEndometriosis is a common uterine disease characterized by the growth of endometrium-like tissue outside the uterine cavity ,9. ApproThis review will cover the known roles of P4 and E2 signaling in maintaining endometrial homeostasis and supporting pregnancy establishment before turning to focus on the mechanisms of the P4 and E2 signaling dysregulation of endometriosis, how this dysregulation impacts the clinical symptoms of endometriosis, and how hormone treatment strategies attempt to correct it.Studies in mice have been critical to understanding the functions of P4 and E2 in the mammalian uterus during early pregnancy ,2,10,11.The basic endometrial function of PGR has been known for some time and recently comprehensively reviewed elsewhere ,12,13,14In response to P4 binding, PGR is capable of rapid, non-genomic action though interaction with c-Src kinase to induce the pro-proliferative extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK) and Protein Kinase B (AKT) pathways, important for peri-implantation stromal proliferation ,23,24. HHomeobox protein-A10 (HOXA10) is another PGR target in the endometrium, and HOXA10 knockout mice are infertile due to uterine defects that appear to be a result of lost stromal P4 responsiveness ,39. InteFoxo1 in the uterus resulted in infertility primarily due to retention of epithelial integrity during the implantation window that prevented embryo invasion [Though many of the important mediators and targets of uterine P4 signaling discussed above have been understood for many years, recent research, enabled by genome-wide transcriptome and cistrome analyses, has revealed new insight on P4 signaling regulators and modifiers . Forkheainvasion . Transcrinvasion .Fkbp52 gene in mice resulted in implantation failure resulting from attenuated P4-responsiveness due to a decrease in the binding of PGR by P4 [FK506 binding protein prolyl isomerase 4 (FKBP52) is a P4 signaling regulator from the FK506 binding family of immunophilins that was first found to interact with and promote PGR activity in vitro . TargeteGR by P4 . MoreoveGR by P4 . In vitrGR by P4 .Signal transducer and activator of transcription 3 (STAT3) is a mediator of leukemia inhibitory factor (LIF) signaling  which wiGata2 was conditionally ablated in the mouse uterus followed by genome-wide expression profiling and chromatin immunoprecipitation analysis revealed a large-scale regulatory role for GATA2 in PGR expression and downstream signaling [Gata2 uterine knockout mice were infertile due to implantation and decidualization defects, and further analysis showed that PGR protein and mRNA expression was dramatically reduced by Gata2 attenuation [IHH and sex determining region Y box 17 (SOX17) [GATA binding protein 2 (GATA2), a zinc finger family transcription factor, was originally identified as a PGR target in the mouse uterus via microarray analysis  and lateignaling . Gata2 uenuation . Remarkaenuation . Finally (SOX17) . These r (SOX17) .Sox17 allele [Sox17 in PGR-positive cells and uterine epithelial cells [Ihh gene [SOX17 is a transcription factor identified as a PGR target by chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) . It was 7 allele  and condal cells . More deal cells . FurtherIhh gene . AdditioIhh gene . A furthIhh gene . ARID1A Ihh gene .P4 signaling in the endometrium cannot be considered on its own without also discussing the counteracting and sometimes cooperating action of E2 signaling. E2′s action in the endometrium is primarily enacted through the binding of its cognate nuclear receptors, estrogen receptor 1 (ESR1/ERα) and estrogen receptor 2 (ESR2/ERβ), which unlike PR-A and PR-B are transcribed from separate genes ,70,71. IThe classic role for E2 in upregulating epithelial proliferation is mediated in part by insulin-like growth factor 1 (IGF1) downstream of ESR1 in the stroma ,88. MechEgr1 knockout mouse studies and human endometrial stromal cell in vitro decidualization experiments have established EGR1 as critical for endometrial receptivity through the regulation of epithelial PGR signaling [In addition to its activity inducing epithelial proliferation, the other critical role for E2 in the endometrium is the induction of LIF, an interleukin-6 family cytokine, in the glandular epithelium by the nidatory E2 spike ,95. Mateignaling , c-Kit eignaling , WNT4 exignaling , and manignaling .SRC-2 resulted in complete female infertility due to implantation failure and a partial loss of decidualization which was completely lost with the concomitant ablation of SRC-1 [Before turning to a focused discussion of P4 and E2 signaling dysregulation in endometriosis, the roles of nuclear receptor coregulators in steroid hormone signaling regulation must be briefly considered. In general, nuclear receptor coregulators form large complexes to modify chromatin structure and regulate large-scale gene transcription programs . A familof SRC-1 ,110. Micof SRC-1 , and traof SRC-1 , supportArid1a ablation also resulted in increased epithelial proliferation concurrent with increased epithelial E2 signaling and decreased epithelial PGR and P4 signaling [ARID1A, a SWItch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex protein, was recently found to be critical for endometrial function during early pregnancy after conditional deletion in the mouse uterus resulted in infertility due to implantation and decidualization defects . Arid1a ignaling . Transcrignaling  and to mEzh2 in the mouse compromised fertility [Hdac3 knockout mice exhibited decreased PGR and PGR target gene expression in the stroma, indicating a role for HDAC3 in the P4-responsiveness required for stromal decidualization [Recent research has highlighted the importance of other epigenetic regulators in addition to ARID1A in endometrial P4 signaling. Enhancer of zeste homolog 2 (EZH2), a polycomb-repressive complex subunit that catalyzes histone 3 lysine 27 trimethylation and leads to gene silencing, was found to be involved in the epigenetic reprogramming required for decidualization . Resultsertility . Anotherertility . Furtherlization .As the work reviewed in the previous sections has demonstrated, tightly regulated signaling pathways governed by P4 and E2 in a stromal and epithelial compartment-specific manner are key to maintaining endometrial homeostasis and supporting female fertility. Dysregulation of steroid hormone signaling is common in many uterine pathologies such as endometriosis, infertility, endometrial cancer, uterine leiomyoma, and recurrent pregnancy loss . For theEndometriosis is classically defined as the presence of endometrium-like tissue located outside the uterine cavity . HoweverWhen endometrial tissue fails to respond properly to P4 exposure, this is termed P4 resistance, and it manifests itself in endometriosis as failed induction of PGR activation, or P4 target gene transcription in the presence of bioavailable P4 ,7. UnderOne potential molecular cause of P4 resistance is a loss or alteration of PGR expression, which has been documented in endometriotic lesions ,129,130 In addition to dysregulated PGR expression, alterations in PGR signaling mediators and regulators also contribute to P4 resistance . Due to Though dysregulation of PGR target genes displays the consequences of P4 resistance in endometriosis, dysregulation of PGR signaling regulators may help explain the cause of P4 resistance. The expression of the pioneer transcription factor FOXO1 is reduced in both the endometrium ,157 and Fkbp52 increased lesion growth [Disruption of PGR signaling in endometriosis could also be caused by dysregulation of steroid receptor chaperone proteins like FKBP52. FKBP52 expression has been found decreased in both the endometrium and lesions of women with endometriosis ,135, andn growth , and in n growth . Evidencn growth .STAT3 is another PGR regulator discussed earlier in this review with an important function in fertility . Given iArid1a in the uterus implicates the decrease of ARID1A in endometriosis in the P4 resistance phenotype as well [Earlier in this review we discussed the importance of the large-scale gene regulatory role for GATA2 and SOX17 in P4 signaling of the endometrium. In endometriosis, there appears to be a switch from a GATA2 driven P4-responsive state to a GATA6-driven P4-resistant state based on CpG methylation patterns . Moreove as well . Express as well . Further as well .Concurrent with P4 resistance, endometriosis development and progression is driven by the upregulation of E2-induced cell proliferation and inflammation, which can both promote lesion growth and compromise endometrial receptivity ,168,169.Since E2′s effects are primarily enacted through ESR1 and ESR2, their expression levels are important in the assessment of E2 action in endometriosis. ESR1 levels are reportedly increased in the secretory phase endometrium of women with endometriosis compared to controls ,173, whiESR1 promoter become hypermethylated, leading to decreased expression [ESR2 promoter becomes hypomethylated, leading to increased expression [In contrast, the majority of the evidence indicates that endometriotic lesions upregulate ESR2 and downregulate ESR1, although reports are mixed ,142,175.pression ,137, whepression . These mThe increase in ESR2 levels in lesions may be responsible for increased lesion survival and inflammation because E2 can act through ESR2 to induce the cyclooxygenase-II (COX-2)-prostaglandin E2 (PGE2) feedback loop , which iIntriguingly, there is also evidence to implicate immune cell responsiveness to E2 in endometriosis. A growing body of evidence has implicated immune system dysregulation in endometriotic lesion growth, one aspect of which is elevated macrophage populations . PeritonIn addition to the targets of E2 and ESRs that induce cell proliferation and inflammation in endometriosis, it is also important to consider the potential effects of SRCs on ESRs in endometriosis. Expression profiling of SRCs in endometriotic lesions identified SRC-1 as the predominant SRC in endometriosis . AlthougAlthough LIF expression is induced by E2 in the endometrium, and estrogenic activity is increased in endometriosis, LIF levels have been reported to be decreased in the glandular epithelium of women with this disease . This coOne of the major clinical pathologies associated with endometriosis is infertility ,193,194.Because of the integral involvement of P4 and E2 signaling pathways in early pregnancy establishment and their dysregulation in the endometriosis-affected endometrium that we have described above, it is intuitive to draw a conceptual link between the P4 resistance and E2 dominance of endometriosis and the endometrial non-receptivity associated with this disease. In addition to the broad conceptual link, several specific molecular pathways we have discussed are implicated in both female infertility and endometriosis. For example, total endometrial PGR expression and PR-A/PR-B expression ratio are critical for successful mammalian pregnancy as shown primarily in mice ,18,19,20The rise in ESR1 in endometriosis corresponds to a decrease in αv/β3 integrin , which iSeveral other steroid hormone-regulated pathways we have discussed are both implicated in endometriosis and closely involved in pregnancy establishment. Proteins involved in regulation and mediation of the P4-responsive IHH pathway including GATA2, SOX17, IHH, COUPTFII, and WNT4 are required for successful implantation in mice ,34,65,67In addition to infertility, it is commonly known that many women with endometriosis experience pelvic pain. Indeed, one study found 80% of women diagnosed with chronic pelvic pain to have endometriosis, firmly establishing the association . SeveralTreatments for endometriosis that aim to alter E2 and P4 signaling are currently in use, such as combined oral contraceptives (COCs), progestins, gonadotropin-releasing hormone (GnRH) agonists, and aromatase inhibitors, and others are still under development, such as GnRH antagonists, selective estrogen receptor modulators (SERMs), and selective progesterone receptor modulators (SPRMs) ,212,213 Several medical treatments for endometriosis directly aim to reduce E2 production or action in order to mitigate E2 dominant conditions. GnRH agonists are normally second-line treatments that decrease hormone levels by downregulating the pituitary through negative feedback mechanisms . In randOther medical treatments for endometriosis primarily center on treating the dysregulation of P4 signaling in endometriosis. COCs consisting of a formulation of E2 and progestins that suppress ovarian steroid production are often used as a first-line therapy for chronic treatment of endometriosis pain due to their practical benefits and safety over long-term use . COCs haWhile progestins are an effective treatment option for many women with endometriosis, P4 resistance renders many others unresponsive to progestin treatment . This diEndometrial homeostasis is clearly tightly interwoven with P4 and E2 signaling. Mutual cooperation and regulation of P4 and E2 pathways is absolutely critical for uterine function and fertility, and when dysregulation of these pathways occurs, pathologies like endometriosis and infertility are common. Recent work enabled by sensitive cistromic and transcriptomic analyses has particularly revealed critical details of P4 and E2 signaling regulators and modulators that are key to maintaining healthy gene regulatory networks in the endometrium. Deepening knowledge of the molecular underpinnings of normal P4 and E2 signaling in the endometrium juxtaposed with the dysregulation in endometriosis that results in E2 dominance and P4 resistance has begun to enable more targeted and individualized treatment options for women suffering the effects of endometriosis, and further study in this area has great potential to unlock treatment opportunities with more permanent efficacy and with fewer adverse effects than currently available therapies can provide.


Cumulative evidence supports a role for neutralizing antibodies contributing to spontaneous viral clearance during acute hepatitis C virus (HCV) infection. Information on the timing and specificity of the B cell response associated with clearance is crucial to inform vaccine design. From an individual who cleared three sequential HCV infections with genotypes 1b, 1a and 3a strains, respectively, we employed peripheral B cells to isolate and characterize neutralizing human monoclonal antibodies (HMAbs) to HCV after the genotype 1 infections. The majority of isolated antibodies, designated as HMAbs 212, target conformational epitopes on the envelope glycoprotein E2 and bound broadly to genotype 1–6 E1E2 proteins. Further, some of these antibodies showed neutralization potential against cultured genotype 1–6 viruses. Competition studies with defined broadly neutralizing HCV HMAbs to epitopes in distinct clusters, designated antigenic domains B, C, D and E, revealed that the selected HMAbs compete with B, C and D HMAbs, previously isolated from subjects with chronic HCV infections. Epitope mapping studies revealed domain B and C specificity of these HMAbs 212. Sequential serum samples from the studied subject inhibited the binding of HMAbs 212 to autologous E2 and blocked a representative domain D HMAb. The specificity of this antibody response appears similar to that observed during chronic infection, suggesting that the timing and affinity maturation of the antibody response are the critical determinants in successful and repeated viral clearance. While additional studies should be performed for individuals with clearance or persistence of HCV, our results define epitope determinants for antibody E2 targeting with important implications for the development of a B cell vaccine. Studies of hepatitis C virus (HCV) infected individuals spontaneously clearing acute infections provide an opportunity to characterize the specificities of associated protective antibody responses. In an individual who resolved three separate HCV infections with different HCV genotypes, the antibodies induced during these acute infection episodes were similar to those induced during chronic infection. Surprisingly, the earliest detected antibodies were directed against conformational HCV epitopes on the envelope glycoprotein E2 (including polyprotein residues 434–446) known to be targeted by broadly neutralizing antibodies. Taken together, the key B-cell determinants in spontaneous clearance are the timing and affinity maturation of broadly neutralizing antibody responses. Over 70 million people worldwide are infected with hepatitis C virus (HCV), with an annual mortality of approximately 400,000 associated with liver failure and hepatocellular carcinoma , 2. EncoWe have addressed these issues by characterizing a panel of human monoclonal antibodies (HMAbs) isolated from peripheral B cells of an individual that sequentially cleared genotypes 1b and 1a HCV infections, as well as subsequently clearing a genotype 3a HCV infection. Neutralizing HMAbs from B cells obtained after resolved infections with genotype 1b and 1a HCV strains demonstrated broad reactivity and targeted overlapping conformational epitopes in highly immunogenic clusters that are similar to those that have been characterized from HCV infected subjects during chronic infections. Interestingly, the earliest neutralizing antibodies induced in this individual were directed against a region on the E2 glycoprotein (including residues 434–446) that is likely to be of low immunogenicity but is highly conserved. The early appearance of these antibodies suggests an important role in viral clearance. Overall, these findings support that natural clearance of acute HCV infection is associated with broadly neutralizing antibodies that are similar to those observed during chronic infection, and that key determinants in spontaneous clearance are the timing and affinity maturation of this response.IL28B rs12979860 polymorphism associated with spontaneous viral clearance . The. The9]. learance . On enro50) at this timepoint even at a reciprocal serum dilution of 100  were tested for binding and neutralizing activities against the autologous 1b isolate and a heterologous 2a isolate . Thus, an of 100 . By contn of 100 , the antn of 100 . Serum aTo further assess the breadth of neutralizing antibody responses, serum neutralization at the same dilutions (with the addition of 1:50) from week 21 to 182 were tested against a panel of 11 heterologous HCVpp –S4 Figs.1 molecules. Of note are that two scFv clones, 212.1.1 and 212.9, accounted for more than 50% of the total clones analyzed. HMAbs 212.1.1 to 212.1.4 have the same VH but different VL. Similarly, 212.2.1 and 212.2.2, as well as 212.3.1 and 212.3.2, respectively have the same VH but different VL. Full-length IgG1 converted HMAbs were initially analyzed for their neutralization against heterologous H77C 1a HCVpp and JFH1 2a HCVcc, and autologous 212 1b HCVpp . Cross-reactivity of the HMAbs was examined against ten E1E2 proteins derived from six different HCV genotypes and subtypes . Broad bΔHVR1 than 212.1.1, 212.10 and HC84.27.To further examine the cross-genotype neutralization potential of HMAbs 212, 212.1.1, 212.10 and 212.25 were tested in dose-response focus forming unit (FFU) reduction neutralization assays  against Broadly neutralizing HMAbs against HCV are predominantly directed against epitopes in E2 (reviewed in ) and epiTo address the question regarding whether the HMAbs isolated from this individual are part of a successful neutralizing antibody response, dilutions of sequential serum samples obtained throughout the course of the first two infections were tested for the presence of these HMAbs. Two antibodies, 212.1.1, and 212.15, were selected representing the antigenic domains B and C-like antibodies that have been isolated. Serum samples from week 21 to 182  were dilTo definitively map the full set of E2 binding determinants of the HMAbs 212.1.1, 212.10, 212.15 and 212.25, we performed global alanine scanning of E2 with these four antibodies, in addition to CBH-5, which is a previously described antigenic domain B HMAb  27]. Ep. Ep27]. To highlight shared and differential residue-level effects on antibody recognition, the four 212 HMAbs are compared with CBH-5 and other HMAbs for four segments on E2  were compared with previously described domain B and C HMAbs  13, 35––35–38. HSeveral of the domain B HMAbs also share a distinctive double-cysteine and double-glycine motif (CxGGxC) in the context of CDR H3 loops ranging from 19 and 27 residues long. Additionally, in four out of five cases, this motif is preceded by a proline residue . The precise cysteine-glycine organization of these HMAbs may be critical for antibody affinity and neutralization; for the AR3C HMAb, which has been structurally characterized in complex with E2, the cysteine residues form a disulfide bond, likely stabilizing the CDR H3 loop in a β-hairpin conformation which makes numerous key hydrophobic contacts and hydrogen bonds with E2 . A searcA conserved region on E2, encompassing aa 412–423 (designated as antigenic domain E), mediates broadly neutralizing antibodies to linear epitopes, but is known to be of lower immunogenicity than other regions . An adjaTo determine the presence of any particular sequence features underlying elicitation of broadly neutralizing antibodies and viral clearance, 212 1b and 212 3a E1E2 sequences were aligned along with H77C and genotype 1a consensus reference sequences, with the latter sequence obtained from the Los Alamos National Laboratory HCV database  Fig 7)..Fig 7). The majority of neutralizing antibodies against HCV are directed against the E2 envelope glycoprotein, because E2 directly interacts with the HCV co-receptors, scavenger receptor class B type 1 (SR-B1)  and the personal communication and manuscript in preparation, A. Lloyd). We believe that both cellular and humoral immunity contributed to the repeated episodes of spontaneous clearance. As for the specificities of the antibody responses, the first indication that these antibodies are directed to conformational epitopes is based on the decrease in serum antibody binding against denatured autologous and heterologous E1E2 recombinant proteins. Autologous and heterologous E2 proteins were employed to isolate a panel of HMAbs. Of 14 antibodies that neutralized at least one of the tested isolates, eight neutralized autologous 212 1b HCVpp and these eight also neutralized at least one of the heterologous isolates. No neutralizing antibodies directed at HVR1 were isolated. This is somewhat surprising since HVR1 is immunodominant. A likely contributing factor is that these antibodies were isolated from a B cell response associated with the second infection with a different isolate, and we screened with autologous E2 from the first infection. A second possible factor is that the subject reported long periods of at least daily injection drug use and sharing of these injections with other users. It is possible that during the 24 months from the initial infection (week 21) to the second infection (week 122), the subject had other undocumented episodes of HCV infection. Thus, the profile of the antibody response at week 123 may reflect multiple exposures to HCV that are associated with repeated viral clearance. This may also pertain to the interval from weeks 123 to 182, underpinning the high serum antibody binding and neutralizing titers maintained during this period.Overall, the studied individual showed a pattern of cross-genotype reactive neutralizing antibodies increasing in titers from the viremic phase to spontaneous clearance of the two first HCV infections. This pattern is consistent with earlier studies on the timing of appearance of broadly neutralizing antibodies response correlating with spontaneous viral clearance , 8. Howein vivo affinity maturation of these antibodies had occurred, and there is no significant bias in the induction of antibodies to these domains. Taken together, these results suggest that antigenic domain B and C antibodies contributed to the protective immunity in this individual. While this immunity did not prevent reinfection, it did potentially prevent progression to chronic infection. Additional studies are required to determine whether these antibodies elicited during acute infection are associated with viral escape, as demonstrated for other HMAbs [In the panel of HMAbs that were isolated, two antibodies, 212.1.1 and 212.9, accounted for more than 50% of the total clones analyzed. These two antibodies and a third, 212.10, are within a highly immunogenic cluster, designated as domain B. Antibodies to overlapping epitopes within this antigenic domain account for the majority of described broadly neutralizing antibodies , and herer HMAbs , 53, 55.IL28B rs12979860 polymorphism that has been associated with spontaneous viral clearance [The studied individual with acute HCV infections also developed antibodies against antigenic domain D. Although domain D antibodies are directed to conformational epitopes, some of these antibodies also bind to synthetic peptides encompassing aa 434–446 . Sequentlearance , 56 raisThe monoclonal antibodies described in this study underscore the importance of features of the human antibody repertoire, including the IGHV1-69 germline gene, in targeting HCV E2. Others recently isolated three IGHV1-69 HMAbs that target antigenic domain B , New South Wales Department of Corrective Services (05/0884), and the University of New South Wales , all located in Sydney, Australia. Written informed consent was obtained from the adult participants.S-transferase was provided by Dr. S. Levy (Stanford University). Anti-CD81 (JS-81) was from BD Biosciences  and anti-core C7-50 was from Abcam .HEK-293T cells were obtained from the ATCC. The Huh7.5 cells, the 9E10 antibody and J6/JFH1 recombinant virus (HCVcc) were generously provided by Dr. C. Rice (Rockefeller University). Dr. T. Wakita  and Dr. J. K. Ball (University of Nottingham) generously provided respectively the 2a JFH1 HCVcc and a panel of genotype 1–6 E1E2 constructs. The CD81 large extracellular loop fused to glutathione Qualitative HCV RNA detection was performed as described . Viral g1 HMAbs have been described previously in details [1 were produced and purified as described [The methods for generating the yeast scFv displayed library, selection of HCV E2-specific scFv and production of scFvs and IgG details . Selectiescribed .HCVcc neutralization was measured with a modified version of an FFU assay as described previously . Serial 3 Huh7.5 cell per well in poly-D-lysine 96-well plates and incubated for 24 hours. Next day, a volume of virus stock corresponding to a read-out of 20–200 FFU per well were incubated in quadruplicates with a dilution series of 212 monoclonal antibodies or relevant positive and negative control antibodies. Virus-antibody mixes along with eight replicates of virus only were incubated for 1 hour at 37°C, then added to Huh7.5 cells and incubated for 4 hours at 37°C and 5% CO2. Subsequently, the cells were washed, and fresh medium was added prior to incubation for a total infection time of 48 hours. Cells were fixed and stained using 9E10 antibody as described previously [The panel represented HCV strains of genotypes 1–6 . We perfeviously , and theeviously . The datHCV-specific antibody detection during the prospective study on subject’s serum samples was conducted as described below for binding to native and denatured E1E2 glycoprotein.Serum samples at specified dilutions were tested for their ability to block the binding of selected HCV HMAbs-conjugated with biotin in a GNA-captured E1E2 glycoproteins ELISA, as described .A standard ELISA was employed to compare serum antibody or HMAb binding to native and denatured HCV E1E2 glycoproteins as described . Brieflyc) binding to native E1E2 glycoprotein.A standard ELISA was employed as outlined above for , after transforming binding percentage data to log ratios, with binding values of 0% set to 0.5% to permit log calculation. E2 positions and antibodies were compared using Euclidean and correlation-based distances, respectively, and clustered using Ward’s minimum variance method. Positions that lacked binding data for one or more HMAbs were removed prior to clustering. Cluster p-values were computed using the approximate unbiased method in the pvclust R package [Hierarchical clustering of alanine scanning data was performed as previously described  using R  package , with 10 package  in R.Antibody nucleotide sequences were analyzed using IMGT/V-QUEST web server  to deterAll protocols were approved by the Institutional Review Board of Stanford University. Ethical approvals were obtained from Human Research Ethics Committees of Justice Health (reference number GEN 31/05), the New South Wales Department of Corrective Services (reference number 05/0884), and the University of New South Wales , and written informed consent was obtained from the study adult participant.S1 Figy-axis) was plotted against the log10 serum dilution (x-axis) for all defined time points listed in the figure legends. A non-linear regression analysis  was performed in GraphPad PRISM v7.02 to calculate the estimated inhibitory concentration required to neutralize 50% of the virus (IC50). The % neutralization was calculated by comparing the RLU of healthy serum to the RLU of the tested serum .The % neutralization ((PDF)Click here for additional data file.S2 Figy-axis) was plotted against the log10 serum dilution (x-axis) for all defined time points listed in the figure legends. A non-linear regression analysis  was performed in GraphPad PRISM v7.02 to calculate the estimated inhibitory concentration required to neutralize 50% of the virus (IC50). The % neutralization was calculated by comparing the RLU of healthy serum to the RLU of the tested serum .The % neutralization ((PDF)Click here for additional data file.S3 Figy-axis) was plotted against the log10 serum dilution (x-axis) for all defined time points listed in the figure legends. A non-linear regression analysis  was performed in GraphPad PRISM v7.02 to calculate the estimated inhibitory concentration required to neutralize 50% of the virus (IC50). The % neutralization was calculated by comparing the RLU of healthy serum to the RLU of the tested serum .The % neutralization ((PDF)Click here for additional data file.S4 Figy-axis) was plotted against the log10 serum dilution (x-axis) for all defined time points listed in the figure legends. A non-linear regression analysis  was performed in GraphPad PRISM v7.02 to calculate the estimated inhibitory concentration required to neutralize 50% of the virus (IC50). The % neutralization was calculated by comparing the RLU of healthy serum to the RLU of the tested serum .The % neutralization ((PDF)Click here for additional data file.S5 Fig50 value (Graphpad PRISM 7.02). J4 and H77ΔHVR1 gave fewer than 20 FFUs/well in virus only wells against all antibodies.Virus stocks of the indicated genotypes 1a and 1b HCV Core-NS2 recombinants were subjected to dose-response FFU reduction neutralization assays using dilution series of the antibodies (A) 212.1.1, (B) 212.10, (C) 212.25, (D) R04, or (E) HC84.27 in quadruplicates with 8 wells of virus only. Following a total of 48 hours infection the cells were immuno-stained and the number of FFUs per well were counted as described in Materials and Methods. Error bars represent standard error of the mean of four replicates normalized to 8 replicates of virus only. The data was analyzed using four-parameter curve-fitting to obtain a sigmoidal dose-response curve, permitting the interpolation of an IC(PDF)Click here for additional data file.S6 Fig50 value (Graphpad PRISM 7.02).Virus stocks of the indicated genotypes 2a and 2b HCV Core-NS2 recombinants were subjected to dose-response FFU reduction neutralization assays using dilution series of the antibodies (A) 212.1.1, (B) 212.10, (C) 212.25, (D) R04, or (E) HC84.27 in quadruplicates with 8 wells of virus only. Following a total of 48 hours infection the cells were immuno-stained and the number of FFUs per well were counted as described in Materials and Methods. Error bars represent standard error of the mean of four replicates normalized to 8 replicates of virus only. The data was analyzed using four-parameter curve-fitting to obtain a sigmoidal dose-response curve, permitting the interpolation of an IC(PDF)Click here for additional data file.S7 Fig50 value (Graphpad PRISM 7.02).Virus stocks of the indicated genotype 3a HCV Core-NS2 recombinants were subjected to dose-response FFU reduction neutralization assays using dilution series of the antibodies (A) 212.1.1, (B) 212.10, (C) 212.25, (D) R04, or (E) HC84.27 in quadruplicates with 8 wells of virus only. Following a total of 48 hours infection the cells were immuno-stained and the number of FFUs per well were counted as described in Materials and Methods. Error bars represent standard error of the mean of four replicates normalized to 8 replicates of virus only. The data was analyzed using four-parameter curve-fitting to obtain a sigmoidal dose-response curve, permitting the interpolation of an IC(PDF)Click here for additional data file.S8 Fig50 value (Graphpad PRISM 7.02). ED43 gave fewer than 20 FFUs/well in virus only wells against 212.10 and 212.25 and SA13 gave more than 200 (but no more than 210) FFUs/well in virus only wells against 212.1.1, R04, and HC84.27.Virus stocks of the indicated genotypes 4a, 5a, or 6a HCV Core-NS2 recombinants were subjected to dose-response FFU reduction neutralization assays using dilution series of the antibodies (A) 212.1.1, (B) 212.10, (C) 212.25, (D) R04, or (E) HC84.27 in quadruplicates with 8 wells of virus only. Following a total of 48 hours infection the cells were immuno-stained and the number of FFUs per well were counted as described in Materials and Methods. Error bars represent standard error of the mean of four replicates normalized to 8 replicates of virus only. The data was analyzed using four-parameter curve-fitting to obtain a sigmoidal dose-response curve, permitting the interpolation of an IC(PDF)Click here for additional data file.S9 Figx-axis) for 30 minutes. After washing, bound antibodies were detected as described in Materials and Methods. The y-axis shows the mean optical density values for triplicate wells, the mean of two experiments ± SD.Recombinant H77C 1a E1E2 lysates were captured by pre-coated GNA wells. After washing and blocking, bound proteins were incubated with each indicated 212 HMAb at 0.005–2 μg/ml ((PDF)Click here for additional data file.S10 Figy-axis). Experiments were performed twice in triplicate. Error bars indicate one standard deviation from the mean.H77C 1a recombinant E1E2 lysate containing 1 μg/ml E2 was incubated with each test HMAb at 10 μg/ml. The antibody-antigen complex was then added onto CD81-LEL-precoated wells. Detection of E2 bound to CD81-LEL was measured with biotinylated CBH-4D , 35–38. (PDF)Click here for additional data file.S11 Figx-axis), a control antigenic domain B HMAb, HC-11, and a no antibody control for 30 minutes. After washing, labeled 212.9 HMAb at 2 μg/ml was added. Bound 212. 9 HMAb was detected as described in Materials and Methods. The y-axis shows the percent competition by each blocking antibody, the mean of two experiments ±SD that were performed in triplicates.Recombinant autologous 1b E1E2 lysates were captured by pre-coated GNA wells. After washing and blocking, bound proteins were incubated with each indicated 212 blocking antibody at 20 μg/ml ((PDF)Click here for additional data file.S12 Fig(A) Approach of HCV cell-cell transmission experiments. HCV Huh7.5.1 producer cells cultured with naïve Huh7.5-GFP target cells were incubated with control or anti-HCV HMAbs (100 μg/ml) in the presence of anti-HCV IgG (50 μg/ml) to block cell-free transmission similar as described . Cell-to(PDF)Click here for additional data file.S1 TableHCV RNA was detected as described in Materials and Methods.(PDF)Click here for additional data file.S2 TableA standard ELISA against of native E1E2 glycoproteins was performed as described in Materials and Methods.(PDF)Click here for additional data file.S3 TableThis study was performed as described in Materials and Methods.(PDF)Click here for additional data file.


By performing first principles calculations combined with the nonequilibrium Green’s function, it is revealed that spin magnetic moments of interfacial atoms suffer a decrease, and the electronic structure shows that the TiNiB-terminated structure possesses the largest interface spin polarization of ≈55%. Our study on spin-transport properties indicates that the total transmission coefficient at the Fermi level mainly comes from the contribution from the spin up electrons, which are regarded as the majority of the spin electrons. When the two electrodes of the CPP-SV device are in parallel magnetization configuration, the interface containing Ti and Ni atoms possesses a higher spin up transmission coefficient than the interface containing Ti and Al atoms. The device with the TiNiB-terminated interface possesses the largest magnetoresistance ratio of 3.28 × 105, and it has great application potential in spintronics devices.A Ti From an experimental point of view, a superconducting spin-valve effect has been demonstrated in a Co2Cr1−xFexAl-based spin valve , where ГL and ГR are the coupling matrix of the left and right electrode, respectively; GR and GA are the retarded and advanced Green’s function of the central region, respectively; and σ is the spin direction, spin up or spin down. A two magnetization configuration is considered, thus the two electrodes of the device are in parallel magnetization configuration (PC) and in antiparallel magnetization configuration (APC). The spin-dependent electron transmission curves of spin up and spin down channels of the device with different atomic terminated interfaces in PC and APC are calculated and shown in ) is much higher than the spin down transmission coefficient at the Fermi level . This reveals that when the device is in the PC state, the spin up channel is unlocked and spin up electrons, which are regarded as the majority of spin electrons, can flow from the left electrode to the right electrode through a Ag spacer. In contrast, the spin down channel is still closed, and the spin down electrons, which are regarded as the minority of spin electrons, are suppressed. Hence, spin-polarized current can be detected when the device is in the PC state, and it is mainly dominated by spin up electrons, and the device is in a “turn on” mode. As for the device with an interface containing Ti and Ni atoms, in the PC state, the value of  in the TiNiT-terminated structure (0.1067) is comparable to the value in the TiNiB-terminated structure (0.1152). In the APC state, the values of  and  in the TiNiT-terminated structure are also close to the values in the TiNiB-terminated structure. Besides, as for the device with an interface containing Ti and Al atoms, the value of  in the TiAlT-terminated structure is 0.0408, and it increases to 0.099 in the TiAlB-terminated structure. Nevertheless, it can be found that the device with the TiNi-terminated interface possesses a higher spin up transmission coefficient than the TiAl-terminated interface.As for our two-probe device, the spin-dependent transmission coefficient kx and ky and indicate the transport behavior of spin up electrons of the device in the PC state. The plots in the middle column and the right column indicate the transport behavior of spin up and spin down electrons, respectively, of the device in the APC state. There are two color bars in kx, ky) points when the device is in the PC and APC state, respectively. It was observed that when the device has different atomic terminated interfaces in the PC state, the magnitude of the hot spots in the spin up channel is much stronger than those in the spin up and spin down channels of the device in APC. This reveals that when the device is in the APC state, the transport ability of spin up and spin down electrons is inhibited, and spin-polarized electrons are less likely to travel from the left electrode to the right electrode. Besides, in the PC state the magnitude of the spin up channel of the TiNiT-terminated structure is comparable to that of the TiNiB and TiAlB structures, while it becomes weaker in the TiAlT termination. This reveals that when the device in the PC state, the spin up electrons of the TiNiT, TiNiB and TiAlB terminated structures have a similar intensity of transport ability, while the transport ability of the spin up electrons of the TiAlT terminated structure suffers from deterioration. Now, the situation when the device is in the APC state will be discussed. It can be seen that in the APC state, the transmission spectra of the spin up channel are nearly the same as that of the spin down channel for all kinds of atomic terminated structures, revealing that the transport ability of the spin up electrons is close to that of the spin down electrons. This results in the consequence that when the device is in the APC state, it is difficult to identify the spin up current and the spin down current from the total spin-polarized current.In order to further exhibit the spin-transport behavior of the device, the transmission coefficient at the Fermi level of various kinds of structures in the two-dimensional Brillouin zone, which is perpendicular to the spin-transport direction, was calculated. In As one the most significant parameters in spintronics devices, the magnetoresistance (MR) ratio (when the device at equilibrium) can be calculated byTPC(Ef) and TAPC(Ef) indicate the total transmission coefficient at the Fermi level in the PC and APC states, wherewhere 2NiAl/Ag/Ti2NiAl device with various kinds of atomic terminated interfaces were calculated and listed in 4 order of magnitude. The device with a TiAlB interface shows a high MR ratio of 6.67 × 104, and the MR ratio is boosted to a higher value of 9.64 × 104 for the TiAlT interface structure. This reveals that for the Ti2NiAl/Ag/Ti2NiAl device with an interface containing Ti and Al atoms, the Heusler layer sits on the top site of the Ag atom and can produce larger a MR ratio than when it sits at the bridge site of the Ag atom. On the other hand, the MR ratio of the device with the TiNiT terminated interface reaches up to 3.03 × 105, and the MR ratio is further enhanced to an ultrahigh value of 3.28 × 105 in the device with the TiNiB terminated interface. Therefore, it can be deduced that the Ti2NiAl/Ag/Ti2NiAl device with the interface containing Ti and Ni atoms generally results in a higher MR ratio than that with interfaces containing Ti and Al atoms. Additionally, the device with a TiNiB-terminated interface possesses the largest MR value and can be regarded as a promising candidate for furture spintronics devices.The MR ratios of the Ti2NiAl/Al/Ti2NiAl CPP-SV and four structures with different atomic terminated interfaces were modeled. Our calculation revealed that the magnetic moments of atoms located at the interface suffer a decrease, while the magnetic moments of atoms that sit at deep layers are close to corresponding values in bulk Ti2NiAl. The TiNiT-terminated structure possesses a high ISP of ≈42%, and the TiNiB-terminated structure has the largest ISP of ≈55%. The total transmission coefficient at the Fermi level mainly comes from the contribution of the spin up electrons, which is regarded as the majority of spin electrons. In the PC state, the spin up transmission coefficients of TiNiT and TiNiB terminated structures are higher than that of TiAlT and TiAlB terminated structures. The MR ratios of the device with four different interfaces, i.e., TiAlT, TiAlB, TiNiT and TiNiB terminated interfaces, have been calculated. Our calculation reveals that the device with TiNiB-terminated structure possesses the largest MR ratio of 3.28 × 105, a value that is much higher than other CPP-SV devices such as Fe4N/Ag/Fe4N and Co2MnAl/Ag/Co2MnAl. Such a high MR ratio could be attributed to the complete spin-polarized Ti2NiAl bulk and high spin polarization at the interface of the device. Therefore, Ti2NiAl/Ag/Ti2NiAl CPP-SV has great application potential in spintronic devices.By employing first principles calculations combined with the nonequilibrium Green’s function, we studied the interfacial magnetic properties, interfacial electronic structure and spin transport properties of a Ti2NiAl/Ag/Ti2NiAl device with four different atomic terminated interfaces was geometrically optimized by utilizing a density functional theory (DFT)-based Vienna ab-initio simulation package (VASP) [d24s2), Ni (3d84s2), Al (3s23p1) and Ag (4d105s1) were chosen to be the valence electron configurations. The exchange-correlation interaction is described by the Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA). A Monkhorst–Pack grid of 13 × 13 × 1 for k-point sampling, a self-consistent field (SCF) convergence criterion of 1 × 10−5 eV, and a plane-wave basis cutoff energy of 550 eV were applied. The Keldysh nonequilibrium Green’s function (NEGF) theory, as implemented in Nanodcal package [2NiAl/Ag/Ti2NiAl device. In our calculations of transport properties, the number of Monkhorst–Pack k-space grids of the left and right electrode is 10 × 10 × 100, and that of the central scattering region is 10 × 10 × 1, where the self-consistent calculations are limited to 10−5 Hartree tolerance.The Tie (VASP) –32. Ti ( package –34, was


Most studies on the fertility transition have focused either on macro-level trends or on micro-level patterns with limited geographic scope. Much less attention has been given to the interplay between individual characteristics and contextual conditions, including geographic location. Here we investigate the relevance of geography and socioeconomic status for understanding fertility variation in the initial phase of the Swedish fertility transition. We conduct spatially sensitive multilevel analyses on full-count individual-level census data. Our results show that the elite constituted the vanguard group in the fertility decline and that the shift in fertility behavior occurred quickly among them in virtually all parts of Sweden. Other socioeconomic status groups experienced the decline with some delay, and their decline patterns were more clustered around early centers of the decline. Long-distance migrants initially had higher fertility than people living close to their birthplace. However, as the fertility decline unfolded, this advantage was either reduced or reversed. This supports the view that migration and fertility are linked in this process. Our results confirm that socioeconomic status differences were of considerable relevance in structuring the fertility transition. The degree to which spatial distance fostered spatial variation in the fertility decline seems to have been negatively correlated with socioeconomic status, with the pattern of decline among the elite showing the lowest degree of spatial variation.The online version of this article (10.1007/s13524-018-0737-9) contains supplementary material, which is available to authorized users. Second, the new behavior must be culturally accepted (willingness). Third, the technical means for preventing conception and the knowledge of those means must be available (ability). Although scholars have debated whether these preconditions are universally applicable , an indirect fertility measure traditionally defined as the number of children aged 0–4 per woman aged 15–49 , farmers (HISCLASS 8), skilled workers (HISCLASS 7), lower-skilled workers (HISCLASS 9–10), unskilled workers (HISCLASS 11–12), and individuals who could not be allocated to a specific class (others). The three further aggregated groups, for which we map the fertility decline and run separate models, are as follows: the elite (HISCLASS 1–6), farmers (HISCLASS 8), and workers and others . Szreter  argued tOne challenge is that although the fertility decline was unfolding dynamically in space and time, our detailed data come in a cross-sectional form that allow insight into net fertility only at specific times during the fertility transition. Therefore, we cannot directly identify individual and contextual factors that shaped fertility changes. Instead, we investigate how statistical associations between net fertility and individual- and parish-level characteristics shifted during the fertility transition. We are, however, able to map the spatiotemporal fertility dynamics by SES in the first descriptive part of our analysis. To our knowledge, this is the first time that geographically detailed maps on the fertility transition by SES are presented for an entire country.In the second part of our analysis, we run separate regression models for 1880, 1890, and 1900 to estimate the associations between net fertility and SES and other individual- and parish-level characteristics.y is the number of children aged 0–4 of a woman w in parish i, α is an intercept, and ζ is a random effect for each parish i. X represents a vector of individual-level covariates, Z is a vector of parish-level covariates, and ε is the error term.where the dependent variable Because we run regression models on geographically highly detailed data, spatial autocorrelation might introduce bias due to the violation of regression assumptions. One important assumption is that the observations are independent. This assumption is often violated in spatial models, given that adjacent units are likely to share many characteristics. If the models are unable to control for the factors that cause this so-called positive spatial autocorrelation, residuals with high or low values will be spatially clustered. Positive spatial autocorrelation might bias parameter estimates and deflate standard errors downward, with the latter resulting in overly optimistic statistical significance tests Anselin .x and y in each parish i, it examines the correlation between the values of a variable y in each parish i with information on the values of the same variable y in the parishes j that are adjacent to parish i. The Moran’s I can take values ranging from –1  to 1 . The closer it is to 0, the less we are faced with spatial autocorrelation. Our Moran’s I tests use spatial weight matrices that define the five nearest parishes j as neighbors, giving each neighbor equal weight.To explore whether our models might be affected by spatial autocorrelation, we derive the Moran’s I indexTable One of the innovative elements of our study is that we account for the lifetime net migration background .Figure Other parish-level covariates that capture socioeconomic conditions include female labor force participation, educational orientation, degree of industrialization, and population density. The latter also serves as a proxy for urbanization. We assume that all four variables are negatively related to fertility during the transition  for all women and our three SES groups. We map the patterns at this higher administrative level to reduce random noise due to small local sample sizes.The vanguard role of the elite might be related in part to their concentration in big cities, which often constituted early fertility decline centers. The maps in Fig. When we disaggregate the numbers by our three SES groups  had the lowest net fertility. This result does not fit with our expectation that women living far from their birthplace were forerunners in the fertility decline. However, this pattern shifted over time. In 1900, women who were born abroad had significantly lower fertility than women in our reference category, and the differences between women in the reference group and women living more than 50 km away decreased substantially. This pattern appears to be even more pronounced in the models for elite women Table , which sTo explore our supposition that long-distance migrants—and especially those living in densely populated contexts—had greater incentives to reduce their fertility, we specified additional models in which we included an interaction between individual-level migration background and population density. The outcomes see the  suggest Among the contextual parish-level variables, we frequently observe the emergence or the strengthening of a significant negative gradient in the association with fertility levels. Such developments are visible for female labor force participation and population density, and to some extent also for education and the proportion employed in industry. The regional dummy variable accounts for unexplained fertility variation around the three biggest cities In assessing whether our main model outcomes are biased by unaccounted spatial autocorrelation in the residuals, we see two potential problems of concern. The first is that the detected remaining spatial autocorrelation might cause bias in our estimates. The second is that especially in the models for the different SES groups, in which the numbers of women in specific locations can be quite small, we might find it difficult to isolate statistical signals for spatial autocorrelation from random noise.To explore the first potential problem, we conducted sensitivity checks with conditional autoregressive models that allowed us to integrate the remaining spatial autocorrelation into the random effects see the . The outWe also performed a number of additional consistency checks. These included models in which we dropped the dummy variable for children aged 5 and older because of the aforementioned endogeneity concerns. Furthermore, we specified models in which we excluded the more sparsely populated northern part of Sweden, given that this region might have differed from central and southern Sweden. Finally, we specified models in which we exchanged our dependent variable with a CWR that considers only children under age 1. This allowed us to determine whether the model outcomes would differ if they were no longer affected by potentially selective mortality above age 0. These consistency checks, which are presented in the In this study, we have explored the relevance of geography and social status for understanding fertility variation at the onset of the Swedish fertility transition. In addition to corroborating previous findings that the elite was a vanguard group, we show that the spatial fertility decline pattern was more homogenous for the elite than for other SES groups. These outcomes suggest that among the elite, access to information relevant to the adoption of fertility-controlling strategies was less constrained by spatial distance. Meanwhile, farmers and workers and others lagged behind in both central and peripheral areas. In many locations, the net fertility of the non-elite groups was still rising when the net fertility of the elite had already begun to decline . The areas where non-elite groups experienced an early decrease were also much more clustered around the early centers of the decline. These findings are in line with Szreter’s  notion oIn interpreting the results, it is important to stress that although our analyses enable us to detect associations between variables, they do not allow us to identify causal effects. For example, the associations between the two variables that capture migration background and our dependent variable could also be related to the presence or absence of fertility events early in life, which may in turn have affected migration decisions at later stages of the life course. In the We also found support for our expectation that long-distance migrants were among the pioneers of the process. However, these results are difficult to interpret. Our finding that fertility was initially higher among long-distance migrants than among women living close to their birth parish might be linked to healthy-migrant effects, or to migration potentially providing women with better access to assets. The observation of a temporal tendency among long-distance migrants toward having a smaller fertility advantage or even lower fertility levels might be related to the higher social connectedness and lower social embeddedness of these migrants. But we also cannot rule out the possibility that long-distance migrants had particularly ambitious goals for themselves and their offspring that made them more open to reducing their fertility. Our models allowed us to investigate the structural consideration that the large number of long-distance migrants clustered in big cities might have had greater incentives to reduce their number of offspring given that they might have had less access to property ownership and local family networks of support. The outcomes suggest that these factors were not important for the elite but might have been relevant for all SES groups taken together and for workers and others. Another possible explanation for the observed shifts concerns changes in unobserved compositional characteristics. The share of long-distance migrants was growing in this period. However, given that this increase was not very large, we consider it rather unlikely that changes in compositional characteristics drove these patterns. We hope that future research will provide more definite answers about the determinants of the observed shifts.In line with the adjustment perspective, another potential explanation for the spatially more homogenous decline pattern of the elite is that they were more likely to be influenced not only by changes in local conditions but also by developments in distant places. For example, changes in career opportunities in Stockholm may have been relevant for the elite who were living far from the capital: these families might have been able to provide their offspring with access to the education their children would need to take advantage of these new opportunities. However, in the context of this argument, it is unclear whether the quality-quantity trade-off was really of great relevance for the elite, given that this SES group was the least constrained by financial limitations  became popular among both farmers and workers


Mice null for both Cx40 and Panx1 produced litter sizes and adult growth progression similar to wild-type (WT), Cx40−/− and Panx1−/− mice. Akin to Cx40−/− mice, Cx40−/−Panx1−/− mice exhibited cardiac hypertrophy and elevated systolic, diastolic, and mean arterial blood pressure compared with WT and Panx1−/− mice; however assessment of left ventricular ejection fraction and fractional shortening revealed no evidence of cardiac dysfunction between groups. Furthermore, Cx40−/−, Panx1−/−, and Cx40−/−Panx1−/− mice demonstrated impaired endothelial-mediated vasodilation of aortic segments to increasing concentrations of methacholine (MCh) compared with WT, highlighting roles for both Cx40 and Panx1 in vascular endothelial cell (EC) function. Surprisingly, elevated kidney renin mRNA expression, plasma renin activity, and extraglomerular renin-producing cell populations found in Cx40−/− mice was further exaggerated in double knockout mice. Thus, while gestation and gross development were conserved in Cx40−/−Panx1−/− mice, they exhibit cardiac hypertrophy, hypertension, and impaired endothelial-mediated vasodilation that phenocopies Cx40−/− mice. Nevertheless, the augmented renin homeostasis observed in the double knockout mice suggests that both Cx40 and Panx1 may play an integrative role.Connexins (Cxs) and pannexins (Panxs) are highly regulated large-pore channel-forming proteins that participate in cellular communication via small molecular exchange with the extracellular microenvironment, or in the case of connexins, directly between cells. Given the putative functional overlap between single membrane-spanning connexin hemichannels and Panx channels, and cardiovascular system prevalence, we generated the first Cx40 Fractional shortening was calculated as: FS (%) = (LVIDd − LVIDs)/LVIDd * 100.Mouse echocardiography was performed as previously described . M-Mode n=7–8 per group). Primers were as described by Wagner et al. (2007) [Kidneys were homogenized in TRIzol reagent . The aqueous layer formed after chloroform addition was purified for RNA using an RNeasy kit  with DNase treatment. cDNA was synthesized using Superscript VILO  with identical RNA inputs for all samples. qPCR was performed on cDNA using PowerUp Sybr Green Master Mix  on a Bio-Rad CFX 96   for reni−/−, Panx1−/−, and Cx40−/−Panx1−/− mouse aortic rings were assessed by performing isometric tension experiments on a wire myograph as previously described [3, 10.0 mM glucose, 4.70 mM KCl, 1.17 mM MgSO4, 1.18 mM KH2PO4, 1.60 mM CaCl2, and 0.027 mM EDTA). Contractile responses to phenylephrine (PE) (1 nM to 30 μM) and potassium chloride (KCl) (10–100 mM) were recorded in vessels stretched to a passive resting tension of either 1000 or 1250 mg. These conditions were determined from earlier pilot experiments. Similarly, dilatory responses were assessed with either methacholine (MCh) (0.1 nM to 30 μM) or sodium nitroprusside (SNP) (0.01–30 nM) in PE (10 μM) pre-contracted rings.Vascular reactivity of WT, Cx40escribed ,50. Thren=6–7 per group). For the renin activity assay, 25 μl of plasma was added to 95 μl of buffer . Synthetic renin substrate  was added to a final concentration of 1 μM and PMSF protease inhibitor was added to a final concentration of 1 mM. Tubes were incubated on ice to assess native renin via endogenous angiotensin I levels or incubated for 1 h at 37°C to assess active renin levels. Angiotensin I was measured using ELISA as per manufacturer’s instructions .Blood was collected via cardiac puncture with EDTA and centrifuged to isolate plasma . Means were deemed statistically significant when Panx1 mRNA found in brain tissue. This is consistent with a report demonstrating that Panx1 protein is found in both rodent atrial and ventricular myocytes [−/− mice  and after maturation in 3-month-old adults (P<0.0001–0.001). Left and right kidney weights were also assessed and found to be similar amongst all four genotypes . Furthermore, we demonstrated that in vivo systolic and diastolic left ventricular thickness was also greater in Cx40−/− and Cx40−/−Panx1−/− mice, predominantly the anterior LV wall (see P<0.01–0.05) as measured by M-mode echocardiography.Given the enlarged appearance of Cx40e hearts A, it wasenotypes D. To detmeasured A,B. Quan−/−, Panx1−/−, and Cx40−/−Panx1−/− mice compared with WT. Immunoblotting indicated similar levels of collagen 1 and fibronectin in atria and ventricle homogenates amongst all four genotypes  which may manifest as changes in Cx43 location. However, the distribution of Cx43 gap junctions and N-cadherin at the ICDs in the atria . Interestingly, heart rates were found to be similar across all genotypes . Nevertheless, EC-independent vasodilation in response to SNP was unaltered amongst all four genotypes ; however, Cx40−/−Panx1−/− mice demonstrated elevated renin expression compared with all other genotypes . Interestingly, Panx1−/− mice exhibited kidney renin mRNA expression levels similar to WT mice (−/− mice demonstrated a 104% increase in plasma renin activity compared with WT (P<0.05), as expected; however, plasma renin activity levels of Cx40−/−Panx1−/− mice surpassed that of Cx40−/− by 57% (P<0.05). Further investigation of renin expression at the level of the glomeruli was assessed using confocal fluorescence microscopy  was impaired across all knockout models compared with WT. Conversely, we observed no differences in SMC-mediated vasoconstriction of aortic segments to PE (α1 adrenergic receptor agonist) or KCl across all genotypes, nor were there differences in EC-independent vasodilatory responses to SNP. These findings implicate a role for both Cx40 and Panx1 in mediating vasodilatory mechanisms in the EC wall. Previously, both Cx40 and Panx1 have been localized to ECs in conduit arteries, are implicated in modifying vasodilatory mechanisms, and conduit arteries of Cx40esponses ,9,21,63.nication . Previou WT mice . Previou/− mouse  or saphe−/− mouse have identified a crucial role for Cx40 in regulating renin secretion and negative feedback inhibition, as these mice exhibit adverse renin secretion and renin-producing cell distribution compared with WT mice [−/− and Cx40−/−Panx1−/− mice, kidney renin expression and plasma renin activity were enhanced in mice lacking both Cx40 and Panx1 compared with Cx40−/− mice. This also correlated with Cx40−/− and Cx40−/−Panx1−/− mice exhibiting elevated kidney renin mRNA levels compared with Panx1−/− and WT mice, where renin expression in Cx40−/−Panx1−/− mice surpassed that of Cx40−/− by 1.6-fold. Plasma renin activity levels were similarly elevated in Cx40−/− mice compared with WT, but again were even greater in Cx40−/−Panx1−/− mice. Further examination of renin expression via confocal fluorescence microscopy revealed that Cx40−/− mice exhibit ectopic localization of renin-producing cells outside the juxtaglomerular region and into the extraglomerular intersitium, previously demonstrated in Cx40-deficient mice [−/−Panx1−/− mice, where renin-producing cell populations extended further around the extraglomerular region. Previous work using Cx40−/− mice and renin producing cell-specific Cx40−/− mice have established that Cx40 is essential for controlling the positioning of renin cells in the juxtaglomerular area [−/− mice expressing Cx40 only in EC (via crossing with Tie2-Cx40 mice expressing Cx40 solely in EC) did not demonstrate an improved blood pressure or renin phenotype [−/− mice are generated to re-express Cx40 in renin-producing cells, yet this adjustment does not correct the displacement of renin-producing cells within the juxtaglomerular area [−/− and Cx40−/−Panx1−/− mice however, renin-producing cells appear in abnormal ectopic locations surrounding the glomerulus other than the juxtaglomerular region, and thus renin-responsiveness of the juxtaglomerular apparatus becomes disrupted. This may suggest that Cx40 in conjunction with Panx1 may be necessary for the appropriate homing of renin-producing cells and regulated renin secretion, but within the field, Cx40 deficiency and renin cell displacement is still not understood. In the current study, the global absence of Panx1 alone did not alter renin mRNA expression, suggesting that renin synthesis is unaffected possibly due to the continued presence of Cx40, further suggesting an integrated role of Cx40 and Panx1 at the level of renin-producing cell localization and regulation. Functionally, little is known about the role of Panx1 in the renal system; however, based on its localization within the renal vasculature, and its role in purinergic signaling, it has been previously hypothesized that Panx1 may play a role in pressure natriuresis [Previous studies using the systemic Cx40 WT mice ,65–67. Ient mice ,65–67. Hlar area ,66–68, alar area ,62,65,69henotype . Blood plar area . In Cx40riuresis . Further−/− and Cx40−/−Panx1−/− mice exhibited enlarged hearts and comparable levels of cardiac hypertrophy due to cardiomyocyte enlargement and thickening of the LV wall; an outcome that was not compounded by impaired LV contractility, cardiac fibrosis, or disruption of molecular components at the ICDs. Likewise, both the Cx40−/− and Cx40−/−Panx1−/− mice demonstrated similar levels of hypertension, while Panx1−/− mice were normotensive. Assessment of vascular reactivity demonstrated that all knockout genotypes exhibited impaired EC-mediated vasodilation compared with WT, highlighting the functional role of Cx40 and Panx1 in the EC layer of the vasculature. Most interestingly, Cx40/Panx1 ablated mice had kidney renin expression levels and plasma renin activity levels that exceed Cx40 null mice, which coincided with aberrant ectopic localization of renin-producing cell populations to the extraglomerular interstitium. These novel findings uncover a potential integrative relationship between Cx40 and Panx1 in the juxtaglomerular apparatus of the kidney and regulation of renin.In summary, the generation of the first systemic Cx40/Panx1 knockout mouse revealed cardiovascular phenotypes similar to mice lacking Cx40. Both Cx40


Understanding cellular responses via signal transduction is a core focus in systems biology. Tools to automatically reconstruct signaling pathways from protein-protein interactions (PPIs) can help biologists generate testable hypotheses about signaling. However, automatic reconstruction of signaling pathways suffers from many interactions with the same confidence score leading to many equally good candidates. Further, some reconstructions are biologically misleading due to ignoring protein localization information.LocPL, a method to improve the automatic reconstruction of signaling pathways from PPIs by incorporating information about protein localization in the reconstructions. The method relies on a dynamic program to ensure that the proteins in a reconstruction are localized in cellular compartments that are consistent with signal transduction from the membrane to the nucleus. LocPL and existing reconstruction algorithms are applied to two PPI networks and assessed using both global and local definitions of accuracy. LocPL produces more accurate and biologically meaningful reconstructions on a versatile set of signaling pathways.We propose LocPL is a powerful tool to automatically reconstruct signaling pathways from PPIs that leverages cellular localization information about proteins. The underlying dynamic program and signaling model are flexible enough to study cellular signaling under different settings of signaling flow across the cellular compartments. Such interactomes are useful for studying the topology of signaling pathways by forming static networks and focusing on the interconnections between proteins and how signals flow between them. In particular, interaction data have enabled the development of methods that aim to link extracellular signals to downstream cellular responses.A fundamental goal of molecular systems biology is to understand how individual proteins and their interactions may contribute to a larger cellular response. Repositories for experimentally derived or manually curated human protein-protein interaction (PPI) information –7 have bMost methods that link signals with responses were initially applied to yeast studies –10. A hak-shortest paths from any receptor to any transcriptional regulator, and the collection of these paths constitute a pathway reconstruction. PathLinker reconstructions have been shown to outperform other pathway reconstruction methods on human networks , and every interaction is predicted to occur within some cellular compartment according to ComPPI. LocPL uses the ComPPI database to restrict the interactions of the interactome by removing edges with an interaction score of zero – these interactions could take place from a biophysical perspective, but are less likely to occur within the cell due to the predicted protein localization. After this filtration step, all edges in the interactome have a non-zero probabilistic score aggregated across all cellular compartments. For subsequent steps of LocPL, we use the ComPPI localization scores that reflect individual proteins in specific cellular compartments.Signaling pathway analysis methods typically take an interactome as input, represented as a graph LocPL’s core method is a k-shortest path algorithm previously described as PathLinker [G, a set R of receptors and a set T of transcriptional regulators (TRs) for a pathway of interest, and a number of paths k, PathLinker outputs a ranked list of the k shortest paths, Pi= is comprised of m nodes that begin at a receptor (v1∈R) and ends at a TR (vm∈T). Each path Pi is ranked by the product of its edge weights (its reconstruction scoreri), and ri≥ri+1 for every i. Note that the shortest path is the one whose edge weights product is the highest among all paths since PathLinker takes the negative log-transform of the edge weights at the reconstruction step.thLinker . Given aLocPL breaks ties in the candidate list of paths Pi, a dynamic program identifies the signaling scoresi of the most likely series of compartments for each node that is consistent with the signaling flow model. After this step, each path Pi will have two scores: a reconstruction score ri computed by PathLinker and a signaling score si computed by the dynamic program. The signaling score is used to re-prioritize the tied reconstruction scores by partitioning the paths into ties  and reordering the paths within each group in decreasing order of the signaling score , which represents where a receptor may be located, Cytosol, and Nucleus. Second, we assume a unidirectional signaling flow from ExtMem through Cytosol to Nucleus. Third, multiple interactions may occur within the same cellular compartment (e.g. multiple interactions may occur within Cytosol). Fourth, signaling flow advances through either interacting proteins that share the same cellular compartment, or a protein that can traverse different cellular compartments. These assumptions impose an ordering on the compartments that must be visited, which we will use in breaking tied paths. Figure a is valid; however, path b is not valid because signaling goes directly from the cellular membrane to the nucleus and path c has one invalid interaction because signaling goes in a direction against the assumed signaling flow.In order to use protein localization information in pathway reconstructions, we first state some assumptions about the pathways we aim to reconstruct. First, we only consider intracellular signaling that begins with activation of a membrane-bound protein receptor and is transmitted to a DNA-binding transcription factor through PPIs within the cytosol. Hence, we focus on three cellular compartments: a combination of extracellular fluid and cell membrane  that connects m proteins, our goal is to find a selection of compartments that maximize the path signaling score  while respecting the assumed signaling flow structure outlined above. For each protein v∈V, we use ExtMem, Cytosol, and Nucleus respectively. We log-transform these scores to be localization costs, that is, v and each cellular compartment c . Let s be the optimal score of the path up to node vj∈P, where vj is in compartment c. The optimal signaling score of the path must end in the nucleus, which we denote by s. Since our assumed signaling model requires that signaling advances through pairs of interacting proteins sharing a cellular compartment or through proteins that traverse multiple compartments, there are only three routes for the signaling information to advance from protein vm−1 to end up in the nucleus for protein vm: 1) protein vm−1 and protein vm interact in the cytosol and then protein vm moves to the nucleus, 2) protein vm−1 moves from the cytosol to the nucleus and then interacts with protein vm in the nucleus, or 3) protein vm−1 and protein vm interact in the nucleus. Based on these constraints, the optimal path signaling score s can be computed as:Given a path vj, j=2,3,…,(m−1), the set of equations for the scores are:In general, at node ExtMem from another protein in ExtMem, we can reach a protein in Cytosol from another protein in either ExtMem or Cytosol, and we can reach a protein in Nucleus from another one in either Cytosol or Nucleus.Note that we can only reach a protein in ExtMem, the base case for these recurrence relations are:To ensure that the path starts with the cellular compartment s since we require the path to terminate in the nucleus. These recurrence relations can be calculated using a dynamic program in linear time w.r.t. the path length for each tied path. An illustrative example of this dynamic program is provided in Additional file The final score taken will be G, a set R of a path starting points (e.g. cellular membrane receptors) and a set T of ending points ), and a fixed number l representing the path length (number of vertices), the color-coding method randomly assigns to each vertex in the graph a uniformly distributed color (label) from {1,2,…,l}, and then finds a colorful path that starts at a receptor (v1∈R), ends at a TR (vl∈T), and each one of the l vertices composing the path has a distinct color. The constraint of a colorful path (distinct colors of the path vertices) ensures that the reconstructed path is simple. The random designation of colors to the vertices leads to an optimal/sub-optimal solution, if one exists. So, a large number of iterations is required to increase the probability of finding a colorful path. The number of iterations increases exponentially with increasing the probability of success and/or the path length [Color-coding is a randomized technique that computes simple paths that start and end at two different vertices and no vertex is visited more than once . Given ah length . Enhanceh length –31.The method described in  extends LocPL produces k paths: the k-shortest paths. In order to compare LocPL against CC, we need CC to produce the same number of paths, where k=20,000 in this study. This in turn requires running CC a number of iterations much larger than k to account for the trials of non-colorful paths. This can take up to days, if not weeks, for a single pathway when the interactions network is very large. The sped up versions of CC mentioned above were tested against relatively smaller networks with hundreds or a few thousands of edges, and many of them may need much modification to integrate the proteins cellular information. So, we augment CC with Yen’s algorithm [k-shortest paths based on the CC method. We call this the Yen_CC method. Once Yen’s algorithm finds a path, it searches for alternative paths that differ from the discovered path in one or more edges. In other words it searches for new partial paths. Hence, in Yen_CC, instead of running a new iteration to find a complete colorful path, the iteration will look for a partial colorful path, leading to reduction in the search space and time. Yen_CC does not handle tied reconstructions, and it reports paths with the same reconstruction cost in an arbitrary order in the k-paths list. Details about how we implemented the CC method and how we augmented it with Yen’s algorithm are provided in the Additional file lgorithm  to compuPLNet2Interactome. We built PLNet2 from both physical molecular interaction data  and annotated signaling pathway databases  [PLNet2 contains 17,168 nodes, 40,016 directed regulatory interactions, and 286,250 bidirected physical interactions, totaling 612,516 directed edges. We assigned interaction direction based on evidence of a directed enzymatic reaction  from any of the source databases. Each interaction is supported by one or more types of experimental evidence (e.g. yeast two hybrid or co-immunoprecipitation), and/or the name of the pathway database. Edges are weighted using an evidence-based Bayesian approach that assigns higher confidence to an experiment type database if it identifies interacting proteins that participate in the same biological process [P of positive edges and a set N of negative edges, the method estimates, for each evidence type t, the probability that t supports positive interactions. These probabilities are then combined for each interaction supported by  evidence types to produce a final weight. We chose the GO term “regulation of signal transduction” (GO:0009966) to build a set of positive interactions that are likely related to signaling. Positives are edges whose nodes are both annotated with this term, and negatives are randomly selected edges whose nodes are not co-annotated to the term. We chose |N|=10×|P| negative edges. To lessen the influence of very highly-weighted edges, we apply a ceiling of 0.75 to all weights [d SPIKE) –37. PLNe process . Given an” GO:000966 to buHIPPIE Interactome. HIPPIE (Human Integrated Protein Protein Interaction rEference) is a repository of 16,707 proteins and 315,484 PPIs [th, 2017 [484 PPIs  . Each ith, 2017  to integGround Truth Pathways. We consider a set of four diverse pathways from the NetPath database [α6β4 Integrin, IL2, EGFR1, and Wnt. Receptors and TRs are automatically detected for each of the eight pathways from lists of 2,124 human receptors and 2,286 human TRs compiled from the literature; see [database  as our gure; see  for moreLocPL compared to PathLinker (PL) and Yen_CC using two methods that evaluate global and local features of the ranked paths.We assess the performance of Precision-recall (PR) curves. Given a ranked list of paths, we order each interaction by the index of the path in which it first appears. We compute precision and recall for this ranked list using the NetPath interactions as positives and a sampled set of negative interactions that are 50 times the size of the positive set.Path-based assessment. The PR curves provide a global quantitative assessment across all the k paths in a reconstruction, showing how quickly (in terms of k) the technique can discover new positive edges. However, this approach considers a positive only once, i.e., the first time it appears in a path. Thus, this global measure fails to characterize each path individually in terms of the number of positives contained in that path. Hence, we introduce a simple way to “locally” assess paths by computing the within-path percentage of true positive edges, denoted as PosFrac. Since we compute this metric value independently for each path, it does not matter if a positive interaction is detected earlier in another path. We compute the PosFrac value over non-overlapping windows of paths. For example, for a window of 100 paths, we compute the average PosFrac over the first 100 paths, then the average PosFrac over the second 100 paths, and so on, providing k/100 values to plot.Statistical significance. The global assessment is based on two concurrent values: precision and recall. These two quantities are related, so we use their harmonic mean (F1 score) to get a single value summarizing both values:prei and reci are the i-th values of precision and recall, respectively. The F1 score values are fed to the Mann-Whitney U (MWU) statistical test for unpaired samples to estimate whether the difference in results between LocPL and PL, and between LocPL and Yen_CC is statistically significant. The inputs to the MWU test for the path-based assessment are the PosFrac values. We acknowledge that PosFrac, precision and recall are not purely independent between the two methods, so there is some dependence introduced in the MWU tests.where PLNet2 have localization information, producing an interactome with about 86% of the edges  in HIPPIE have this information  and LocPL to signaling pathways from the NetPath database to the PLNet2 and HIPPIE interactomes as described in the “k=20,000 paths for each approach, similar to the original publication [si distribution for paths with the same reconstruction score ri. Signaling scores are used to re-order paths sharing the same reconstruction score. We also computed 20,000 paths using the Yen_CC approach for the PLNet2 interactome only due to the very long time needed to run Yen_CC. We show results for the PLNet2 interactome first and then show those for HIPPIE.We applied PathLinker  of the two values in Fig. F1 curve for LocPL is significantly higher than that of PL and Yen_CC for the four pathways .For every value of precision and recall, we plotted the harmonic mean  for PL and Yen_CC, PosFrac for LocPL dominates the graph . In the IL2 pathway reconstruction, this distinction is significant  to the HIPPIE interactome. Figure LocPL is greater than that for PL, and that the proportions of positives detected by LocPL is always higher than those of PL. This consistently leading performance of LocPL over PL is evidently statistically significant  to green (cytosol) to blue (nucleus), and second, no paths of length one are allowed. Both of these features are visible in the comparison of the IL2 pathway reconstructions , Insulin Like Growth Factor 1 Receptor (IGF1R), Leptin Receptor (LEPR), KIT Proto-Oncogene Receptor Tyrosine Kinase (KIT), and Erythropoietin Receptor (EPOR). Further, the Interleukin 6 Signal Transducer (IL6ST) is also reported to be at the membrane, yet is downstream of Suppressor Of Cytokine Signaling 3 (SOCS3) in the network  use proLocPL ensures that the constituting interactions, from a receptor to a TR, are spatially-coherent within the different cellular compartments. This feature increases the number of paths that contain positives early in the pathway reconstruction, which supports our hypothesis that LocPL locally promotes paths with higher proportions of positives up in the k-shortest paths list . There are many ways to impose a compartmental ordering of signaling flow to capture other features of signaling, including mitochondria-dependent signaling, nuclear receptor signaling and extracellular signaling. LocPL is generalizable to different signaling models, as long as the user specifies compartment relationships in a memoryless manner . To illustrate this point, we developed a model of signaling that also includes the mitochondria compartment. We did not notice any changes in the results when we included the mitochondria into our signaling model, most likely due to the relatively few number of proteins in PLNet2 that had non-zero Mitochondria localization scores (Additional file In this work, we chose to impose an ordering on a subset of the available compartments from ComPPI (Visual inspection of the subgraphs containing the first 100 paths in the pathway reconstructions before and after applying the dynamic program reveal that reordering tied paths changes the first 100 paths dramatically, even though the number of nodes and edges remain similar (Additional file LocPL, which is a powerful tool for automatic reconstruction of signaling pathways from protein-protein interactions that leverages the proteins cellular localization information. LocPL showed profound and significant better reconstructions over those by peer methods in terms of the total number of the true protein interactions across the whole pathway reconstructions and the number of positive interactions per individual paths with a reconstruction. The framework that we have developed may be extended to other graph-theoretic approaches that return subnetworks of directed structure with an associated reconstruction score, such as trees [In this study, we presented as trees , 11, 15.Additional file 1 This file includes the additional material referred to through the main manuscript.