Red cell membrane stiffness in iron deficiency

The purpose of this study was to characterize red blood cell (RBC) deformability by iron deficiency. We measured RBC deformability to ektacytometry, a laser diffraction method for determining the elongation of suspended red cells subjected to shear stress. Isotonic deformability of RBC from iron-deficient human subjects was consistently and significantly lower than that of normal controls. In groups of rats with severe and moderate dietary iron deficiency, RBC deformability was also reduced in proportion to the severity of iron deficiency. At any given shear stress value, deformability of resealed RBC ghosts from both iron-deficient humans and rats was lower than that of control ghosts. However, increase of applied shear stress resulted in progressive increase in ghost deformation, indicating that ghost deformability was primarily limited by membrane stiffness rather than by reduced surface area-to-volume ratio. This was consistent with the finding that iron-deficient cells had a normal membrane surface area. In addition, the reduced mean corpuscular hemoglobin concentration (MCHC) and buoyant density of the iron-deficient rat cells indicated that a high hemoglobin concentration was not responsible for impaired whole cell deformability. Biochemical studies of rat RBC showed increased membrane lipid and protein crosslinking and reduced intracellular cation content, findings that are consistent with in vivo peroxidative damage. RBC from iron-deficient rats incubated in vitro with hydrogen peroxide showed increased generation of malonyldialdehyde, an end-product of lipid peroxidation, compared to control RBC. Taken together, these findings suggest that peroxidation could contribute in part to increased membrane stiffness in iron- deficient RBC. This reduced membrane deformability may in turn contribute to impaired red cell survival in iron deficiency.     

A case of chromoblastomycosis with an unusual clinical manifestation caused by Phialophora verrucosa on an unexposed area: treatment with a combination of amphotericin B and 5-flucytosine

Chromoblastomycosis is a cutaneous and subcutaneous mycotic disease caused by the dematiaceous (black) fungi. Five species of fungi are known generally to be the cause: Fonsecaea pedrosoi, Phialophora verrucosa, Cladosporium carrionii, F. compacta and Rhinocladiella cerphilum. In infected tissue they can appear as pigmented sclerotic bodies, commonly called 'copper pennies', which are pathognomonic of chromoblastomycosis. The infection usually occurs through traumatic skin inoculation, with the majority of lesions occurring on the feet and legs of outdoor workers. We report a patient in whom the lesions had begun on the right breast, which is an unexposed area, without a history of trauma. A uniform, reliable treatment does not exist but our patient was mycologically cured with the use of amphotericin B and the subsequent combination of 5-flucytosine and itraconazole.     

Efficacy of Random-start Controlled Ovarian Stimulation in Cancer Patients

This study aimed to evaluate the efficacy of random-start controlled ovarian stimulation (COS) in cancer patients for emergency fertility preservation. In this retrospective comparative study, 22 patients diagnosed with cancer and 44 infertile women undergoing conventional in vitro fertilization (IVF) were included. In cancer patients, ovarian stimulation was started on the day of referral, irrespective of their menstrual cycle date. The control group was selected by age matching among women undergoing conventional IVF. COS outcomes were compared between groups. The number of total and mature oocytes retrieved and the oocyte maturity rate were higher in the random-start group than in the conventional-start group. However, duration of ovarian stimulation was longer in the random-start group (11.4 vs. 10.3 days, P = 0.004). The addition of letrozole to lower the estradiol level during COS did not adversely affect total oocytes retrieved. However, oocyte maturity rate was lower in cycles with letrozole than in cycles without letrozole (71.6% vs. 58.2%, P = 0.019). Our study confirms the feasibility and effectiveness of random-start COS in cancer patients.

Graphical Abstract

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Decreased Serum Epinephrine in Children With Positive Skin Prick Test

Objectives

To evaluate the association between catecholamine levels and skin prick test results among children.

Methods

Two hundred eight first grade children from one elementary school were invited to participate in this study. Skin prick test (SPT) for six allergens (2 house dust mites, cat, dog, mugwort, and pollen mixture) was performed, and patient demographic information was recorded. The parents were surveyed using questionnaires about rhinitis-related symptoms. Finally, venous blood sampling was done to measure catecholamine levels (epinephrine, norepinephrine, and dopamine) by high-performance liquid chromatography.

Results

Out of 208 children, 174 (106 boys and 68 girls) enrolled in this study. Ninety-six of the children (55%) had negative SPT (nonsensitization group), while 78 (45%) had a positive SPT to at least one of six allergens (sensitization group). The diagnosis of chronic rhinitis was more prevalent in the sensitization group (35.9%) than nonsensitization group (26.0%), however the finding was not significant (P=0.186). Epinephrine levels were decreased between the sensitization group compared to the nonsensitization group (P=0.004). There was no difference in norepinephrine and dopamine levels (P>0.05).

Conclusion

Epinephrine levels are lower in children with positive SPT compared to controls, however, the level of the catecholamine was not associated with the presence or absence of rhinitis symptoms.     

Linked selection and recombination rate variation drive the evolution of the genomic landscape of differentiation across the speciation continuum of Ficedula flycatchers

Speciation is a continuous process during which genetic changes gradually accumulate in the genomes of diverging species. Recent studies have documented highly heterogeneous differentiation landscapes, with distinct regions of elevated differentiation (“differentiation islands”) widespread across genomes. However, it remains unclear which processes drive the evolution of differentiation islands; how the differentiation landscape evolves as speciation advances; and ultimately, how differentiation islands are related to speciation. Here, we addressed these questions based on population genetic analyses of 200 resequenced genomes from 10 populations of four Ficedula flycatcher sister species. We show that a heterogeneous differentiation landscape starts emerging among populations within species, and differentiation islands evolve recurrently in the very same genomic regions among independent lineages. Contrary to expectations from models that interpret differentiation islands as genomic regions involved in reproductive isolation that are shielded from gene flow, patterns of sequence divergence (d_xy and relative node depth) do not support a major role of gene flow in the evolution of the differentiation landscape in these species. Instead, as predicted by models of linked selection, genome-wide variation in diversity and differentiation can be explained by variation in recombination rate and the density of targets for selection. We thus conclude that the heterogeneous landscape of differentiation in Ficedula flycatchers evolves mainly as the result of background selection and selective sweeps in genomic regions of low recombination. Our results emphasize the necessity of incorporating linked selection as a null model to identify genome regions involved in adaptation and speciation.Uncovering the genetic architecture of reproductive isolation and its evolutionary history are central tasks in evolutionary biology. The identification of genome regions that are highly differentiated between closely related species, and thereby constitute candidate regions involved in reproductive isolation, has recently been a major focus of speciation genetic research. Studies from a broad taxonomic range, involving organisms as diverse as plants (Renaut et al. 2013), insects (Turner et al. 2005; Lawniczak et al. 2010; Nadeau et al. 2012; Soria-Carrasco et al. 2014), fishes (Jones et al. 2012), mammals (Harr 2006), and birds (Ellegren et al. 2012) contribute to the emerging picture of a genomic landscape of differentiation that is usually highly heterogeneous, with regions of locally elevated differentiation (“differentiation islands”) widely spread over the genome. However, the evolutionary processes driving the evolution of the differentiation landscape and the role of differentiation islands in speciation are subject to controversy (Turner and Hahn 2010; Cruickshank and Hahn 2014; Pennisi 2014).Differentiation islands were originally interpreted as “speciation islands,” regions that harbor genetic variants involved in reproductive isolation and are shielded from gene flow by selection (Turner et al. 2005; Soria-Carrasco et al. 2014). During speciation-with-gene-flow, speciation islands were suggested to evolve through selective sweeps of locally adapted variants and by hitchhiking of physically linked neutral variation (“divergence hitchhiking”) (Via and West 2008); gene flow would keep differentiation in the remainder of the genome at bay (Nosil 2008; Nosil et al. 2008). In a similar way, speciation islands can arise by allopatric speciation followed by secondary contact. In this case, genome-wide differentiation increases during periods of geographic isolation, but upon secondary contact, it is reduced by gene flow in genome regions not involved in reproductive isolation. In the absence of gene flow in allopatry, speciation islands need not (but can) evolve by local adaptation, but may consist of intrinsic incompatibilities sensu Bateson-Dobzhansky-Muller (Bateson 1909; Dobzhansky 1937; Muller 1940) that accumulated in spatially isolated populations.However, whether differentiation islands represent speciation islands has been questioned. Rather than being a cause of speciation, differentiation islands might evolve only after the onset of reproductive isolation as a consequence of locally accelerated lineage sorting (Noor and Bennett 2009; Turner and Hahn 2010; White et al. 2010; Cruickshank and Hahn 2014; Renaut et al. 2014), such as in regions of low recombination (Nachman 2002; Sella et al. 2009; Cutter and Payseur 2013). In these regions, the diversity-reducing effects of both positive selection and purifying selection (background selection [BGS]) at linked sites (“linked selection”) impact physically larger regions due to the stronger linkage among sites. The thereby locally reduced effective population size (N_e) will enhance genetic drift and hence inevitably lead to increased differentiation among populations and species.These alternative models for the evolution of a heterogeneous genomic landscape of differentiation are not mutually exclusive, and their population genetic footprints can be difficult to discern. In the cases of (primary) speciation-with-gene-flow and gene flow at secondary contact, shared variation outside differentiation islands partly stems from gene flow. In contrast, under linked selection, ancestral variation is reduced and differentiation elevated in regions of low recombination, while the remainder of the genome may still share considerable amounts of ancestral genetic variation and show limited differentiation. Many commonly used population genetic statistics do not capture these different origins of shared genetic variation and have the same qualitative expectations under both models, such as reduced diversity (π) and skews toward an excess of rare variants (e.g., lower Tajima''s D) in differentiation islands relative to the remainder of the genome. However, since speciation islands should evolve by the prevention or breakdown of differentiation by gene flow in regions not involved in reproductive isolation, substantial gene flow should be detectable in these regions (Cruickshank and Hahn 2014) and manifested in the form of reduced sequence divergence (d_xy) or as an excess of shared derived alleles in cases of asymmetrical gene flow (Patterson et al. 2012). Under linked selection, predictions are opposite for d_xy (Cruickshank and Hahn 2014), owing to reduced ancestral diversity in low-recombination regions. Further predictions for linked selection include positive and negative relationships of recombination rate with genetic diversity (π) and differentiation (F_ST), respectively, and inverse correlations of the latter two with the density of targets for selection. Finally, important insights into the nature of differentiation islands may be gained by studying the evolution of differentiation landscapes across the speciation continuum. Theoretical models and simulations of speciation-with-gene-flow predict that after an initial phase during which differentiation establishes in regions involved in adaptation, differentiation should start spreading from these regions across the entire genome (Feder et al. 2012, 2014; Flaxman et al. 2013).Unravelling the processes driving the evolution of the genomic landscape of differentiation, and hence understanding how genome differentiation unfolds as speciation advances, requires genome-wide data at multiple stages of the speciation continuum and in a range of geographical settings from allopatry to sympatry (Seehausen et al. 2014). Although studies of the speciation continuum are emerging (Hendry et al. 2009; Kronforst et al. 2013; Shaw and Mullen 2014, and references therein), empirical examples of genome differentiation at multiple levels of species divergence remain scarce (Andrew and Rieseberg 2013; Kronforst et al. 2013; Martin et al. 2013), and to our knowledge, have so far not jointly addressed the predictions of alternative models for the evolution of the genomic landscape of differentiation. In the present study, we implemented such a study design encompassing multiple populations of four black-and-white flycatcher sister species of the genus Ficedula (Fig. 1A,B; Supplemental Fig. S1; for a comprehensive reconstruction of the species tree, see Nater et al. 2015). Previous analyses in collared flycatcher (F. albicollis) and pied flycatcher (F. hypoleuca) revealed a highly heterogeneous differentiation landscape across the genome (Ellegren et al. 2012). An involvement of gene flow in its evolution would be plausible, as hybrids between these species occur at low frequencies in sympatric populations in eastern Central Europe and on the Baltic Islands of Gotland and Öland (Alatalo et al. 1990; Sætre et al. 1999), although a recent study based on genome-wide markers identified no hybrids beyond the F₁ generation (Kawakami et al. 2014a). Still, gene flow from pied into collared flycatcher appears to have occurred (Borge et al. 2005; Backström et al. 2013; Nadachowska-Brzyska et al. 2013) despite premating isolation (for review, see Sætre and Sæther 2010), hybrid female sterility (Alatalo et al. 1990; Tegelström and Gelter 1990), and strongly reduced long-term fitness of hybrid males (Wiley et al. 2009). Atlas flycatcher (F. speculigera) and semicollared flycatcher (F. semitorquata) are two closely related species, which have been less studied, but may provide interesting insights into how genome differentiation evolves over time. Here, we take advantage of this system to identify the processes underlying the evolution of differentiation islands based on the population genetic analysis of whole-genome resequencing data of 200 flycatchers.Open in a separate windowFigure 1.A recurrently evolving genomic landscape of differentiation across the speciation continuum in Ficedula flycatchers. (A) Species’ neighbor-joining tree based on mean genome-wide net sequence divergence (d_A). The same species tree topology was inferred with 100% bootstrap support from the distribution of gene trees under the multispecies coalescent (Supplemental Fig. S1). (B) Map showing the locations of population sampling and approximate species ranges. (C) Population genomic parameters along an example chromosome (Chromosome 4A) (see Supplemental Figs. S2, S4 for all chromosomes). Color codes for specific–specific parameters: (blue) collared; (green) pied; (orange) Atlas; (red) semicollared. Color codes for d_xy: (green) collared-pied; (light blue) collared-Atlas; (blue) collared-semicollared; (orange) pied-Atlas; (red) pied-semicollared; (black) Atlas-semicollared. For differentiation within species, comparisons with the Italian (collared) and Spanish (pied) populations are shown. Color codes for F_ST within collared flycatchers: (cyan) Italy–Hungary; (light blue) Italy–Czech Republic; (dark blue) Italy–Baltic. Color codes for F_ST within pied flycatchers: (light green) Spain–Sweden; (green) Spain–Czech Republic; (dark green) Spain–Baltic. (D) Distributions of differentiation (F_ST) from collared flycatcher along the speciation continuum. Distributions are given separately for three autosomal recombination percentiles (33%; 33%–66%; 66%–100%) corresponding to high (>3.4 cM/Mb, blue), intermediate (1.3–3.4 cM/Mb, orange), and low recombination rate (0–1.3 cM/Mb, red), and the Z Chromosome (green). Geographically close within-species comparison: Italy–Hungary. Comparisons within species include the geographically close Italian and Hungarian populations (within [close]), and the geographically distant Italian and Baltic populations (within [far]). Geographically far within-species comparison: Italy–Baltic. (E) Differentiation from collared flycatcher along an example chromosome (Chromosome 11) (see Supplemental Fig. S3 for all chromosomes). Color codes for between-species comparisons: (green) pied; (orange) Atlas; (red) semicollared; (dark red) red-breasted; (black) snowy-browed flycatcher. Color codes for within-species comparisons: (cyan) Italy–Hungary; (blue) Italy–Baltic. Flycatcher artwork in panel A courtesy of Dan Zetterström.