This study has limitations It

This study has limitations. It is possible that we are missing information on key determinants of postpartum AL such as a pre-pregnancy history of cardiovascular disease or pre-pregnancy chronic disease. As we enrolled women postpartum and the focus of our analyses are on the postpartum period, we were unable to account for prior health conditions. Also, in our main analysis, we did not model any of our covariates as mediators. Yet, it is plausible that variables such as stress and resilience could be in the pathway between race/ethnicity and AL. We ran additional models, using approaches that correctly account for mediation (Richiardi et al., 2013), and found neither stress nor resilience mediated the relationship between race/ethnicity and AL. Constraints on participant time and funding limited the assessments we could make. For example, our measure of poverty group incompletely captured economic resources since measures that include assets and debt have been found to be more accurate predictors of health inequalities by race than income or poverty status alone (Braveman, 2008; O’Campo et al., 1997). We also did not account in these analyses for employment (e.g. job titles, occupational status), or other indicators of socioeconomic position that may further explain the inequalities as this information was not in our surveys. Also, budget constraints prevented us from collecting primary data on neighborhood stressors identified by our CC-10004 partners as being important to postpartum stress, including pollution, crime and safety, public transportation, social disorder, housing affordability, child care availability, employment opportunities, and community resources. Many of these will be correlated with the variables we did include in our Neighborhood Indices. Yet, had this information been available we might have been able to create unique indicators for rural, suburban and urban settings as the literature and a concept mapping activity across the five sites suggested that the importance of those stressors differed by type of setting (Schaefer-McDaniel et al., 2010; Laraia et al., 2006). Unfortunately, these measures are unavailable through secondary data (e.g., census) but could be investigated in future research using neighborhood observational data (Schaefer-McDaniel et al., 2010).
Despite these limitations, this is the most comprehensive, multilevel, longitudinal study of stress and women\’s health inequalities to date, unique in its careful assessment of multiple stressors and resilience resources (Dunkel Schetter et al., 2013), as well as the only study on postpartum health and allostatic load. We relied on strong participation from our cross-site community partners into many aspects of the study from selection of key constructs and measures to ensuring that the perspectives and desires of our respective diverse communities as to topics of and procedures of study were being represented (Ramey et al., 2015; Shalowitz et al., unpublished manuscript; Dunkel Schetter et al., 2013; O’Campo et al., 2016). Finally this study is unique in taking an inequalities approach in analyses by attempting to explain them, rather than only reporting on the magnitude of the disparities. CCHN\’s community and multidisciplinary scientists and practitioners are responsible for these innovations.
Once accounting for economic, psychological (stress and resilience), neighborhood, and medical condition variables, our models explained 45% of the inequalities between Whites and African Americans and 43% between non-Hispanic Whites and Latinas. There are various possibilities for why these variables did not fully explain AL inequalities between African American and Latinas as compared to Whites. One is that we did not examine other key social determinants of health such as housing affordability or employment and other factors mentioned above that often vary by race and ethnicity in the US. Increasingly studies using the life course perspective are documenting importance of adverse and traumatic childhood conditions which we also were not able to capture in our study (Gonzalez et al., 2009; Smith, Gotman, and Yonkers, 2016; Slopen et al., 2015). A final and intriguing possibility is that we have yet to fully conceptualize the sources of these inequalities and that cultural, socioeconomic, psychosocial, and structural factors that underlie them are elusive. This work suggests that all low income mothers are at risk in the postpartum period for a subsequent pregnancy with adversities and for unhealthy aging. Past research has identified several strategies to reduce poverty including raising the minimum wage, expanding the Earned Income Tax Credit, promoting pay equity policies or even a universal unified child credit. These strategies have been identified as helping to close the race disparities in outcomes during the childbearing year (Lu et al., 2010). Future work can further explore what can be done to understand and start early in the life course to eradicate effects of poverty on poor health among ethnic and racial groups given their persistence and the health inequalities involved.

br Conclusions br Acknowledgements br Introduction Poor diet

Conclusions

Acknowledgements

Introduction
Poor diet is an important modifiable contributor to many chronic diseases including childhood obesity (Han, Lawlor, & Kimm; World Health Organization, 2004). Understanding the determinants of dietary behaviour during childhood is important as poor dietary behaviours track from childhood to adulthood (Craigie, Lake, Kelly, Adamson, & Mathers, 2011). Children\’s diet is influenced by individual preferences as well as the wider shared family, social and physical environment, as highlighted by ecological models of health behaviour (Bronfenbrenner, 1997). The contribution of the local food environment to a poor diet is a relatively new area of research. To date, findings are inconsistent and this may be due to conceptual and methodological issues associated with measuring the food environment (Caspi, Sorensen, Subramanian, & Kawachi, 2012; Feng, Glass, Curriero, Stewart, & Schwartz, 2010; Holsten, 2009; Mackenbach et al., 2014).
The food environment is multidimensional (Glanz, Sallis, Saelens, & Frank, 2005) and the availability of food outlets is one important aspect of the local food environment. Research has found that smaller food outlets including convenience stores tend to stock a higher proportion of processed foods, a smaller range of Obeticholic Acid and vegetables, and charge higher prices for food than supermarkets, especially in poorer areas (Kaufman, MacDonald, Lutz, & Smallwood, 1997; MacDonald & Nelson, 1991; Rose & Richards, 2004). Shorter distances to a supermarket and a higher number of local supermarkets are consistently associated with a higher dietary quality in North America, particularly among low income households (Rose & Richards, 2004). Evidence from Europe and Australia is less consistent (Black, Moon, & Baird, 2013) with recent studies finding no difference in food availability between better and worse off communities (Cummins & Macintyre, 1999, 2002), particularly for supermarkets (Maguire, Burgoine, & Monsivais, 2015).
Research on the association between the food environment around children\’s homes and diet is sparse and inconclusive. Engler-Stringer, Le, Gerrard, and Muhajarine (2014) conducted a systematic review which examined the influence of location and accessibility of food outlets on children\’s diet (). Though there was much heterogeneity between studies, the review found some moderate evidence to suggest that the local food environment around households may influence children\’s diet. However, the effect sizes in many of the included studies were small (Engler-Stringer et al., 2014). For example, a study from the UK reported that increasing distance to a convenience store was associated with a slightly lower intake of foods such as chocolate and crisps (Skidmore et al., 2010). Furthermore, in the UK, availability of ‘unhealthy’ food outlets was associated with a higher body mass index (BMI) which is a more distal outcome than diet (Jennings et al., 2011). Leung, Gregorich, Laraia, Kushi, & Yen, 2010 reported an inverse association between the prevalence of food/retail destinations in the neighbourhood environment and total energy intake in girls aged 6–8 years from the USA (Leung et al., 2010). However, there have also been null findings for the association between the local food environment and diet in children (An & Sturm, 2012).
Increasingly, policymakers recognise the potential role of the food environment to curb chronic diseases including obesity and also to encourage healthy eating. Thus, a better understanding of the relationship between local area food availability and dietary quality in children is needed. In 2007, 89% of all eating occasions for Irish children aged 5–12 years occurred at home (Burke et al., 2007) suggesting that food availability around households is important. For the current paper, we hypothesised that greater access to food outlets (closer proximity and the number of supermarkets) would be associated with a higher dietary quality in children. As children may have limited autonomy over food purchase and eating behaviours, we control for family level socio-economic factors to capture aspects of the shared home environment. This paper explores if distance to and the number of food outlets (supermarkets and convenience stores) in the local environment around households are associated with dietary quality in a nationally representative sample of nine year old children controlling for family level socio-economic factors.

A marginal structural model by means of additive

A marginal structural model by means of additive hazard regression was thereafter applied to mortality. Additive hazard regression is a flexible model for survival analyses with the linear dependence of the model facilitating decomposition into direct, indirect, and total effects (Lange & Hansen, 2011). The Aalen additive hazard regression is, in itself, entirely non-parametric with covariate effects varying with time (Aalen, 1989). However, a reduction of the model is feasible using the Mckeague and Sasieni (1994), whereby some coefficients are time-invariant, and the Lin and Ying (1994), whereby all coefficients except the baseline are kept time-invariant. This latter model is by analogy an additive version of the Cox regression model. These methods are implemented in the timereg package in R (Scheike & Martinussen, 2006). Standard tests (Scheike & Martinussen, 2006) for the time dependence of coefficients showed that they could be kept time-invariant, thus, the coefficients were presented as the additional number of deaths per year per 1000 breast cancer patients. Similarly, the cumulative baseline mortality could be seen to increase linearly over time, and is therefore presented as the expected number of deaths per year per 1000 patients for the reference group. Direct and indirect effect estimates as well as effect estimates for the total effects were obtained by conducting a parametric bootstrap resampling with 10,000 replications as described by Nordahl et al. (2014).
To determine the plausibility of the results, a sensitivity analysis was conducted investigating education-specific changes in incidence and by adjusting for the association between education and the risk of dying from causes other than breast cancer. For the analysis of incidence, Poisson regression modeling was used. The purchase topotecan size data contained no information on civil status and parity, as the population at risk was defined as the aggregate population stratified by education, year of diagnosis, age at diagnosis, and year relative to the start of screening in each county. To analyze the association between education and the risk of dying from causes other than breast cancer, all-cause mortality was compared to cancer-related mortality (WHO ICDv10 C00-C97), breast-cancer specific mortality (ICDv10 C50), and excess mortality by subtracting the expected mortality by education level in the general population. The data for the sensitivity analyses are discussed in Appendix C.

Results

Discussion
The scope of this article was to study the role of cancer stage and socioeconomic inequality in mortality. This study is inherently limited in its focus given the complex relationship between SES and breast cancer incidence and mortality in the general population (Yabroff & Gordis, 2003). Indeed, the results are in line with a central purchase topotecan tenet of Yabroff and Gordis which stated that the relationship between SES and mortality is dependent on the relation of stage distribution with SES, which changes upon the introduction of a cancer control program.
The introduction of a public screening program was associated with an increase in the incidence of breast cancer that, to some degree, also had a leveling effect of incidence across education levels. In my view, this is supportive of the main findings in this study, since this suggests, but does not confirm, that groups with lower levels of attained education did indeed benefit more from the technology diffused by the introduction of the NBCSP. The estimates of incidence increase are comparable to those of a recent study investigating changes by cancer stage (Lousdal, Kristiansen, Moller, & Stovring, 2016).
Since the cancer registry has almost complete coverage of breast cancer incidence (Larsen et al., 2009), it follows that one can also use the data source to evaluate cancer and breast-cancer specific mortality as opposed to total mortality. When assessing mortality among breast cancer patients, the results suggested that direct differences (not through cancer stage) in mortality after the introduction of the program were more uniform across education levels, whereas the indirect effects (those through cancer stage) remained similar to results observed in the all-cause analysis. One interpretation of this finding, although not a definitive conclusion, suggests that any previous differences in breast cancer mortality (beyond what can be observed from the relationship between SES and cancer stage) would remain in future investigations, but would be more equal than differences found in analyses examining in all-cause mortality.

Table shows results from models partitioned by

Table 4 shows results from models partitioned by sex. In caspase pathway to the pooled results, Model 2 of Table 4, our fully adjusted model, shows no statistically significant difference in the probability of being a current smoker among the first generation males in the sample by age at migration. This table also shows that relative to the third/higher generation, the probability of being a current smoker is 7.6 percentage points lower for second-generation black males with two foreign-born parents. Among men, there is no statistically significant difference in the probability of being a current smoker among individuals with one-foreign-born and one U.S.-born parent relative to the third/higher generation.
However, our findings suggest that among women, there is a more pronounced increase in current smoking across immigrant generations. For example, the marginal effect for immigrant women who arrived at or before age 13 is 4.6 points greater than the marginal effect caspase pathway for women who migrated after age 13 (Table 4, Model 2, Women). In contrast, there is no statistically significant difference between these two groups for men. Similarly, while there is a sizable second-generation advantage in current smoking among second-generation men with two foreign-born parents, this estimate for women is considerably smaller (-0.076 vs. -0.027) and marginally significant. Similar to men, there is no statistically significant difference in the probability of being a current smoker between third/higher generation women and second-generation women with one foreign-born parent.
Table 5 shows results for our fully specified model for each of the ancestral subgroups. Similar to the full-sample results (Table 3), first-generation immigrants from each of the ancestral subgroups are substantially less likely to report being current smokers relative to the third/higher generation. Among immigrants from Latin America, the magnitude of this association is stronger among first-generation immigrants who came to the United States after age 13 than for those who migrated at or before age 13. Age at migration does not appear to be associated with the probability of smoking among first-generation West Indian, African, and Haitian immigrants.
The second-generation immigrant advantage (relative to the third generation) is largest among individuals with two African-born parents [-0.135 (95% CI: -0.192, -0.078)]. Across each ancestral subgroup, we detect no statistically significant differences in current smoking status between the third/higher generation and second-generation immigrants with only one foreign-born parent. Tables 6 and 7 present these estimates separately for men and women, revealing a similar pattern of smoking as shown in Table 5. Because of the small sample sizes that generate these estimates, however, these results should be viewed with caution.

Discussion, limitations, and conclusion

Introduction
Mental health disorders are a major worldwide public health concern (Murray & Lopez, 2002), and the societal costs of such disorders are high (Ingoldsby & Shaw, 2002). Mental health and behavior problems often originate in childhood or adolescence (Kessler, Berglund, Demler, Jin, Merikangas & Walters, 2005), and may set youth on a negative trajectory of escalating mental health problems (Ingoldsby & Shaw, 2002). Exposure to disadvantaged neighborhoods is associated with poorer mental health (Leventhal & Brooks-Gunn, 2003), yet pectoral girdle remains unknown what specific mechanisms explain why certain neighborhood characteristics influence health (Macintyre, Ellaway, & Cummins, 2002).
We leverage the Moving to Opportunity (MTO) for Fair Housing demonstration, which tested whether receiving a rental voucher to move from disadvantaged neighborhoods improved families’ outcomes, compared to public housing control group families. The MTO study provides strong causal inference and unbiased effects of being offered a housing voucher on outcomes because random assignment ensures that no confounder, measured or unmeasured, is associated with offered treatment, except by chance (Kleinbaum, Sullivan, & Barker, 2007). Moreover, MTO is a policy-relevant treatment, given that over 5 million low-income Americans in over 2 million households use Housing Choice Vouchers, the leading federal affordable housing policy, to subsidize housing costs (Center on Budget & Policy Priorities, 2015). Policy-relevant exposures identify concrete and realistic intervention points that can enhance impacts on health and health disparities (Glymour, Osypuk, & Rehkopf, 2013).

While evolutionary research originally focused on people s general

While evolutionary research originally focused on people\’s general preferences in mate selection and was concerned with the differences between men and women (Buss, 1995; Gangestad & Simpson, 2000), later studies began to examine other issues, such as the length of a relationship. Researchers also began to compare the reasons why individuals preferred short-term relationships (dating, one-night stands) to long-term ones (cohabitation, marriage) (Buss & Schmitt, 1993).
Evolutionary psychologists now consider that women may establish short- or long-term relationships for a variety of reasons which depend on environmental circumstances (Durante et al., 2011). Women in developed ha tag prefer long-term partners who transmit a sense of professional, material and social success, as evidenced in studies that positively correlate suitor\’s preferences and income level, and their degree of job security (Landolt, Lalumière, & Quinsey, 1995). Other studies also corroborate women\’s preference for ambitious suitors focused on their career and ability to earn a high income (Eagly & Wood, 1999). However, women also positively evaluate other signs that men will make good partners and have long-term cooperative attitudes, such as their willingness to invest time in children (Scheib, 2001). Although physical attractiveness is considered to be an important asset, in stable relationships women assign less importance to this than men do (Buss, 1995; Regan, 1998). One of evolutionary psychology\’s main subjects is partner preference in attractive couples, and physical attractiveness and sex appeal are considered to be “honest signals” to opposite-sex members of a mate\’s phenotypic quality (Kirkpatrick, 1996).
However, while the desire for a physically attractive partner may be an instinctive preference, Jensen-Campbell, Graziano, and West (1995) observe that for women a suitor\’s physical attractiveness must be complemented by pro-social behaviour: in short, a ha tag good candidate for a long-term relationship must have favourable financial prospects (Gustavsson, Johnsson, & Uller, 2008) and solid social status (Buss & Schmitt, 1993); the candidate must also be a little older (Buss et al., 1990), ambitious and hardworking (Lund, Tamnes, Moestue, Buss, & Vollrath, 2007); and, finally he must also be strong and attractive (Gangestad & Thornhill, 1997).
On the other hand, the literature observes five basic reasons why women pursue short-term relationships: to obtain material and protective resources; to gain some kind of genetic benefit; to begin the process by which a current partner is eventually replaced; to begin a relationship that may become long-term; and to manipulate a current partner (as a strategy for revenge or deterrence) (Buss, 2014). These reasons also apply in the animal world, where trading sex for resources occurs among primates (Symons, 1980) and in humans in pre-industrial hunter-gatherer societies (Benshoof & Thornhill, 1979). (Note that female primates and women in pre-industrial societies use short-term relationships to attain immediate resources and reduce the time required to forage for their own survival and their offsprings.)
In line with the findings of Scheib (2001), however, in the developed world and modern society, women establish short-term or even extramarital relationships mainly to obtain genetic benefits. Women show similar preferences about their suitors’ personal attributes in short- and long-term relationships (Buss, 1994) but consider physical attractiveness to be more important in the short term (Regan, 1998), where casual partners do not usually offer long-term investments and where the woman\’s main concern is genetic quality. Note that an important physical marker of a suitor\’s health is his degree of face and body symmetry (Gangestad & Thornhill, 1997; Greiling & Buss, 2000; Rikowski & Grammer, 1999) and that another sign of health and genetic quality is facial appearance, where suitors with larger and more pronounced lower jaws, stronger brow ridges and more pronounced cheekbones transmit a greater sense of masculinity (Waynforth, Delwadia, & Camm, 2005).

The studies that were described emphasize the presence of

The studies that were described emphasize the presence of a-MCI and DA. But when we talk about MCI and sleep disorders, there is another group which must be cited. Rapid eye movement (REM) sleep behavior disorder (RBD) is a form of parasomnia characterized by the presence of abnormal and often violent motor manifestations during REM sleep [41]. This abnormal behavior result from disorder of the deep nuclei and brainstem neurons involved in the integration of the sleep–wake cycle and the locomotor system [21]. A lot of researches found a link between RBD and synucleinopathies such as Parkinson disease (PD), Lewy body dementia (LBD) and multiple system atrophy [41,42] and are even considered to be early marker for these diseases [43]. In the consensus criteria for LBD, RBD are considered to be suggestive features of the disease [44]. Besides, a study that analyzes the presence of MCI in patients with PD and RBD show that prevalence of MCI in PD with RBD is 73%. In patients with idiopathic RBD the prevalence is 50%, and in PD patients without RBD this proportion decrease to 11%, nearly the same as control subjects (8%) [45]. With this results, they suggest that the presence of RBD is a major risk factor for MCI. Among the subtypes of MCI, the naMCI single domain and aMCI multiple domain were most associated with PD patients with RBD, both characterized by a predominant impairment of executive functions and attention. When Petersen described the MCI criteria, this etiology was already presumed [3].
The analyzed studies do not mention another important issue: the obstructive sleep PyBOP (OSA). This condition can leads to cognitive deficits mainly in memory and executive functions [46–48]. While OSA does not cause dementia, it could be considered to cause MCI. The patients with OSA is a vulnerable patient due to the entire “package” of daytime somnolence, disordered sleep, subclinical (or clinical) cerebrovascular and cardiovascular disease. So by the possibility of mimics a neurodegenerative disorder and is potentially reversible with treatment, this condition must be investigated and treated in subjects with decline in cognitive functions. Furthermore the e4 allele of apolipoprotein E (APOE), which is a major risk factor for AD [49], has been associated with OSA in adults especially in the setting of cognitive problems [50]. OSA is itself detrimental for cognition, especially among those at greater risk for AD due to their APOE e4 carrier status.

Conclusion

Introduction
The Upper Airway Resistance Syndrome (UARS) was first named by Guilleminault in 1993 [1] while investigating cases of excessive daytime sleepiness with no identified cause in adults. However, the respiratory pattern of increased upper airway resistance was previously identified in pre-pubertal children under the label “sleep-related respiratory resistive load” [2].
Since this first description, many authors have attempted to describe the clinical and polysomnographic features of UARS patients based on their experience, to find a definitive way to diagnose and finally treat them. In particular, during the last twenty years, the definition of UARS has varied (Table 1). Currently, UARS is subsumed under the diagnosis of Obstructive Sleep Apnea Syndrome (OSAS) by the American Academy of Sleep Medicine (AASM) (Berry AASM 2012) [3]. Its diagnostic criterion is still not defined and some authors believe that UARS is part of a continuum between primary snoring and OSAS whereas others believe that it is a distinct syndrome from OSAS. Some authors support that both UARS and OSAS have the same symptoms and as their pathophysiology do not significantly PyBOP differ from each other, UARS is not a distinct disease [4,5]. Nevertheless, other authors believe that UARS patients present different features than other Sleep related Breathing Disorder (SRBD) [6,7,8]. The most frequent symptoms are excessive daytime sleepiness, fatigue and sleep fragmentation. However, UARS patients also present significantly more often with sleep-onset and sleep-maintenance insomnia, postural hypotension, headaches, gastroesophageal reflux, irritable bowel syndrome, anxiety and alpha-delta sleep [9,10,11]. The proportion of women with UARS is also significantly higher than for OSAS [12]. Besides having some different clinical presentation, it has been suggested that UARS and OSAS differ from each other in terms of their sleep EEG and autonomic nervous system responses. Some authors believe that UARS patients have an increase in alpha rhythm and an over-activation of the autonomic nervous system [13].

Finally we found that macroscopic analysis of whole tumours

Finally, we found that macroscopic analysis of whole tumours could predict response, and baseline Ktrans was the strongest predictor, which suggests VEGF is main determinant of vascular leakiness, though not necessarily angiogenesis. Although baseline gene expression did not strongly correlate with MRI variation, once an environmental stress was induced there was strong concordance between imaging and mRNA changes, enabling patient classification by gene response linked to imaging changes with therapy implications. Control theory indicates difficulty of relating response to baselines if rules for connection are unknown, but our results show how quickly tumours adapt and then allow the characteristics to be defined.
We conclude that bevacizumab has been prematurely discontinued, rather than focusing on finding subgroups of patients who most benefit using monitoring during 2week window before continuing therapy. This would be cost-effective and help stratify patients for combination or other targeted therapies.
Finally, we suggest new paradigms for clinical research. Firstly, trials should incorporate appropriate initial enrichment of patients with high Ktrans, and a range of therapeutic options to meet potential early resistance pathways induced. Then, early imaging will be needed to stratify patients into categories likely to have different mechanism of adaptation, and biopsies to select patients for appropriate combinations. Repeatability of these assays makes this widely feasible. Multi-arm adaptive trials are ongoing using molecular markers for targeted agents, but Necrostatin 1 we suggest this needs to be further modified by much earlier Necrostatin 1 when using drugs affecting the tumor microenvironment.

Introduction
Cell-free DNA (cfDNA) refers to nucleic acids detected in body fluids and are thought to arise from two sources: passive release through cell death (Jahr et al., 2001), and active release by cell secretion (Stroun et al., 2000). DNA from cancer cells also contributes to the total load of cfDNA (Schwarzenbach et al., 2011), and the fraction of cfDNA that comes from cancer cells is called circulating-tumor DNA (ctDNA). ctDNA has been estimated to make up about 0.01%–1% of cfDNA for early-stage disease, reaching over 40% for late-stage disease (Beaver et al., 2014; Bettegowda et al., 2014; Couraud et al., 2014; Diehl et al., 2007; Forshew et al., 2012; Newman et al., 2014; Sausen et al., 2015). Despite its intrinsic limitations, including technical issues in the sample collection, detection, and identification of tumor origin, ctDNA is emerging as a key potential biomarker for monitoring response to treatment and relapse (Dawson et al., 2013; Esposito et al., 2014; Forshew et al., 2012; Garcia-Murillas et al., 2015; Murtaza et al., 2013; Roschewski et al., 2015; Siravegna et al., 2015). The potential of ctDNA is not limited to post-diagnosis surveillance but it may also play a crucial role in the detection of pre-clinical cancer. If successful, this could be translated into much improved cancer survival, in particular for those cancer sites that are typically diagnosed at a late stage, and for which survival is poor, such as lung, pancreatic, or esophageal cancer (Brennan and Wild, 2015). However, implementation of ctDNA tests that detect pre-clinical disease in a non-symptomatic population will have to show an extremely high specificity if they are to provide meaningful results, or be part of a multi-modal screening program.
Very few studies have focused on the evaluation of ctDNA detection in early-stage cancers (i.e. stage I-II tumors) with even less data available on the detection of ctDNA in blood samples from pre-symptomatic cancer patients (Amant et al., 2015; Beaver et al., 2014; Bettegowda et al., 2014; Garcia-Murillas et al., 2015; Gormally et al., 2006; Jamal-Hanjani et al., 2016; Sausen et al., 2015); Table S1). In addition, these studies have aimed to detect specific mutations in cfDNA (most of them using digital droplet PCR) following previous assessment of the tumor mutational profile. This approach is only viable for cancers with common hot-spot mutations and is not amenable for most screening purposes. This is because early detection of pre-clinical cancer requires variant detection to be done without prior knowledge from tumor tissue of the expected mutations. Another limitation of these studies is the major assumption that circulating-mutated fragments would be absent (or very rare) in individuals without cancer. Demonstrating that any ctDNA detection marker has a specificity close to 100% would be of fundamental importance for large-scale utility in an asymptomatic population (Wentzensen and Wacholder, 2013).

The recent findings clearly demonstrate the mutagenic effect of

The recent findings clearly demonstrate the mutagenic effect of ribavirin on the HEV genome, which can lead to an emergence of distinct viral populations (Debing et al., 2014, 2016b; Gisa et al., 2015; Todt et al., 2016). These distinct viral populations resulted from ribavirin treatment failure may cause a more complicated clinical outcome, extrahepatic manifestations and may have different transmission patterns. Development of a new antiviral therapy or/and combination with an alternative therapeutic option (eg. PegIFNα, Sofosbuvir) may help to increase the efficiency of treatment course and to reduce the treatment failure risk as well as to avoid the emergence of the viral populations associated with drug resistance and fulminant liver failure. Investigating potential HEV mutations related to resistance to new antiviral therapies are recommended. In clinical practice, systematic examination of HEV FK866 variants by next-generation sequencing should be considered for any clinical relevance, which may associate with treatment failure, chronic and fulminant infections to predict therapy outcomes and in the progression of liver diseases.

Conclusions and Perspectives
Although HEV infection is largely controlled by host immune responses, viral factors including HEV genetic variability associate with the clinical course, host adaption, and antiviral resistances. Different HEV genotypes exhibit a selective host range with unique transmission patterns and pathogenesis. Deletion/insertion, recombination and substitutions occurring in the HEV genome can influence HEV replication and virus-host interaction, and be subsequently associated to pathogenesis (Table 1 and Fig. 2). Under host immune pressure, clinically relevant non-synonymous and silent mutations occurring throughout the entire HEV genome may be associated with severe forms of the disease and potentially anti-viral resistances (Table 2 and Fig. 2). Ribavirin treatment failure is associated with the RdRp mutations Y1320H, K1383N, D1384G, K1398R, V1479I, Y1587F and G1634R. The mutations Y1320H and G1634R contribute to decreased susceptibility to antiviral drugs by enhancing HEV replication and infectivity, whereas the other mutations (eg. K1383N) likely reduce viral replication and increases ribavirin sensitivity. These mutations may affect the efficiency of viral RdRp activity; however, the precise role of these identified mutations remains unclear. Except for the drug resistance-related HEV mutations in the RdRp domain, most mutations in other regions found in clinical isolates do not corroborate with results from artificial mutations in functional studies, thus suggesting the nature of mutational complexity. Further studies will help to elucidate the possible contribution of HEV variants in HEV physiology, pathogenesis and clinical relevance.

Conflict of interest

Author\’s contributions

Financial support
HVT would like to acknowledge financial support from the European Association for the Study of the Liver (EASL) through the Andrew K. Burroughs fellowship during the research exchange at the Robert Koch Institute, Berlin, Germany. BW was supported by the China Scholarship Council (CSC), Beijing, China. The content is only the responsibility of the authors and does not represent the views of EASL or CSC.

Introduction
Allergen-specific immunotherapy (AIT) is the only disease-modifying treatment for allergy which prevents the progression of allergic rhinitis towards asthma (Larché et al., 2006, Jacobsen et al., 2007). Clinical and immunological effects of AIT are long-lasting, even after discontinuation (Durham et al., 1999). Furthermore, AIT has a cost-saving effect when compared to symptomatic drug treatment (Hankin and Cox, 2014). However, several factors limit the broad application of AIT. Current allergy vaccines are based on natural allergen extracts which are often of poor quality (e.g., varying allergen compositions, lack of important allergens, contaminations) and may induce severe immediate and late phase side effects (Focke et al., 2008, Casset et al., 2012, Winther et al., 2006, Focke et al., 2010). Accordingly current treatment schedules require inconvenient, multiple administrations of gradually increasing doses and, in sensitive patients, the therapeutically effective maintenance dose often cannot be reached due to side effects. As a result, the real-life adherence to AIT is low (Kiel et al., 2013).

B cell activation including the activation of pre existing memory

B cell activation, including the activation of pre-existing memory B cells (MBC), contributes to a substantial plasmablast response during acute heterologous infection [7–9], resulting in a high increase in neutralizing antibody titers [10] that contribute to temporary cross-protection against all four serotypes. Recently, we demonstrated that this plasmablast response is polyclonal, but all purchase crf hormone cloned from the genes of individual plasmablasts recognized the envelope (E) glycoprotein. In contrast, the majority of previously reported DENV-specific MBCs isolated from the blood of recovered dengue patients were specific to either prM, a membrane protein expressed on immature, non-infectious virus particles, or to non-structural proteins, notably NS1 [11–14], potentially indicating separate pathways of development between plasmablasts and classical MBCs.
The establishment of multiple levels of B cell memory has been suggested previously in mice. It was observed that IgM+ germinal center (GC) derived MBCs re-entered GC reactions upon re-infection, whereas IgG+ GC-derived MBCs almost exclusive differentiated into plasmablast [15]. Another elegant study in wild-type mice documented the generation of two distinct memory populations after immunization with the model antigen phycoerythrin: a long-lasting IgM memory population and a more short-lived IgG memory population. Upon re-immunization, switched memory cells differentiated into plasmablasts and proliferated to increase the memory B cell pool without further affinity maturation [16]. In contrast, the response of IgM memory B cells after re-immunization was inhibited by high amounts of specific IgG in the serum masking the antigen [16]. In B cell receptor (BCR)-transgenic mice, the formation of plasmablasts was facilitated by high affinity binding to the BCR [17][18], a high antigen-to-B cell ratio, and a strong BCR signal [19,20], but this system is limited in that only one epitope can be studied. During a natural viral infection, B cells respond to multiple viral epitopes, and antibodies with both high and low neutralizing capacities can have similar affinities [21]. Thus, affinity alone does not determine the efficacy of an anti-viral response, and the different biological functions of plasmablasts versus memory B cells and long-lived plasma cells post primary infection are not clear.
In humans, plasmablasts appear in the blood five to seven days after infection or vaccination. Human plasmablasts have been studied extensively to monitor vaccine- or natural infection-induced specific B cell responses and to generate disease-specific human monoclonal antibodies [8,22–26]. Moreover, the plasmablast response was reported to be predictive of antibody titers at least during early convalescence [22,24]. Lavinder et al. studied whether plasmablasts or MBCs contributed to the serum antibody pool after tetanus vaccination and found little repertoire overlap, concluding that only a small fraction of plasmablasts and MBCs contributed to long-lived humoral immune memory [27].

Methods

Results
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Discussion
Immune memory allows for the efficient activation and expansion of B cells during recall responses. It has long been established that a recall B cell response involves rapid generation of plasmablasts and a temporally delayed formation of germinal centers. It is less clear, however, which B cells enter each path, and how the plasmablast and classical memory B cell population is related during acute stages of infection. We find here that plasmablast and memory B cell formation after DENV re-infection involves clonally distinct B cells. The clonally related sequences were all of the IgM isotype and could represent B cells that bound to DENV with low affinity and that were enriched during the sorting with fluorescently labeled virus. This binding could be cognate or via heparan sulfate, which is a receptor for DENV. Although DENV-binding cells were sorted from the CD27+ memory B cell population (Fig. S1) we cannot exclude that few naïve CD27− naïve B cells were also included in the memory gate. The accumulation of IgM+ cells in the DENV-binding but not the control memory B cell pool (Fig. 2E) further points to an enrichment of low affinity IgM B cells. We did not have a pentameric IgM expression system and were not able to verify the binding of the MBC-DENV–derived IgM antibodies. A role of IgM MBCs in maintaining memory over prolonged periods of time and the capacity of IgM MBCs to re-enter germinal centers is intriguing [15,16] but will have to be studied in more detail in the context of dengue.

A second interesting conclusion that can be drawn

A second interesting conclusion that can be drawn from our work concerns the paradoxical effect of PIO on Hq versus WT mice. PIO, a widely used hypoglycaemic drug, acted as predicted for a PPARγ ligand in WT mice, therefore decreasing glycaemia and weight, without significantly affecting motor performance. Conversely, the blood glucose levels, which were sub-normal in untreated Hq mice, increased under PIO treatment with the result that several Hq mice displayed blood glucose levels similar to WT. Incidentally, hypoglycaemia is an inconsistent feature of RC deficiency in humans, but low glycaemia is seldom mentioned in RC deficient mice. Yet, the ablation of TFAM in the mouse skeletal muscle results in RC defect, decreased blood glucose, increased glucose tolerance and insulin-independent skeletal glucose uptake (Wredenberg et al., 2006). Interestingly enough, most of the PIO treated Hq mice that normalized their glycaemia also restored their muscle strength to control values. The paradoxical effect of PIO on glycaemia of Hq mouse may be tentatively ascribed to a reduction of glucose utilization resulting from the inhibition of the glycolytic enzyme GAPDH. Targeting of GAPDH by PIO was confirmed by in vitro experiments involving astrocytes derived from Hq mice or cultured fibroblasts derived from two patients harboring loss-of-function mutations affecting the RC-sustaining function of AIF. Beside its interaction with the PPARγ receptor (Dovinova et al., 2013; Gray et al., 2012), additional PIO targets have been reported at the level of pyruvate metabolism (Divakaruni et al., 2013; Ye et al., 2016). Nonetheless, none of these putative targets appeared to mediate the beneficial effects of PIO on blood glucose levels in Hq mice. Instead, GAPDH turns out as a supplemental target that is directly inhibited by PIO in vitro and that is downregulated in Hq mice treated with PIO in vivo, as well as in cultured astrocytes from Hq mice or AIF-mutant fibroblasts exposed to PIO in vitro.
The genetic mao inhibitors of the Hq mice presumably gave us the opportunity to recognize PIO Hq responders, and to ultimately identify GAPDH as one additional PIO target. With the aim to further document the effect of PIO in RC-deficient mice, the isolation of PIO-responsive congenic Hq strains and/or the identification of PIO-responsive alternative RC-deficient mice can be considered in future years. The positive effect of PIO observed in Hq mice is reminiscent of the neuroprotection conferred by PIO in humans, in which PIO reportedly lowers the incidence of dementia among non-diabetic individuals (Heneka et al., 2015) and reduces neuroinflammation in multiple sclerosis (Negrotto et al., 2016). Considering these factors, the potential effect of PIO on patients affected by mt disease should be examined. Biomarkers that may guide the inclusion and maintenance of patients in such trials evaluating PIO may include blood glucose levels, as well as the modulation of GAPDH expression in peripheral tissues.

Funding Sources
This work was supported by French (ANR AifInter to PR and GK) (ANR-11-BSV1-0017) and European (E-rare Genomit to PB and PR) (16-CE18-0010-02) institutions, and patient\’s associations to PB and PR: Association Française contre les Myopathies (AFM; Project No. 11639), Association d\’Aide aux Jeunes Infirmes (AAJI), Association contre les Maladies Mitochondriales (AMMi), Association Française contre l\’Ataxie de Friedreich (AFAF), and Ouvrir Les Yeux (OLY).

Conflicts of Interest

Author Contributions

Introduction
Atrial natriuretic peptide (ANP) is a member of the natriuretic peptide family comprising also B-type and C-type natriuretic peptides. Together with B-type natriuretic peptide, ANP is expressed mainly in the cardiac atria and secreted to circulation upon cardiac strain; accordingly, increased circulating concentrations are seen in heart failure settings (Mukoyama et al., 1991). In the last decade, however, these cardiac hormones have also been implicated in metabolic dysfunction, where decreased circulating concentrations have been reported in obesity, insulin resistance, and diabetes (Jujić et al., 2016; Then et al., 2013; Wang et al., 2007).