Sadder but fitter. The evolutionary function of depressive symptoms following fetal loss

A literature review about an evolutionary model of fetal loss depression is presented. This model conceptualizes depression following miscarriage or stillbirth as an evolutionary protective mechanism to avoid further fetal loss. It postulates that depressive symptoms delay the next reproduction and save maternal resources. These symptoms along with hypochondric symptoms of depression which lead to a search for causes and reappraisal of environmental factors, are probably adaptations to causes of further fetal loss (e.g. epidemics, famines, infections, environmental toxins)

Robustness of the charge-ordered phases in IrTe2{\mathrm{IrTe}}_{2} against photoexcitation

We present a time-resolved angle-resolved photoelectron spectroscopy study of IrTe2, which undergoes two first-order structural and charge-ordered phase transitions on cooling below 270 K and below 180 K. The possibility of inducing a phase transition by photoexcitation with near-infrared femtosecond pulses is investigated in the charge-ordered phases. We observe changes of the spectral function occurring within a few hundreds of femtoseconds and persisting up to several picoseconds, which we interpret as a partial photoinduced phase transition (PIPT). The necessary time for photoinducing these spectral changes increases with increasing photoexcitation density and reaches time scales longer than the rise time of the transient electronic temperature. We conclude that the PIPT is driven by a transient increase of the lattice temperature following the energy transfer from the electrons. However, the photoinduced changes of the spectral function are small, which indicates that the low- temperature phase is particularly robust against photoexcitation. We suggest that the system might be trapped in an out-of-equilibrium state, for which only a partial structural transition is achieved

Macroscopic phase segregation in superconducting K_0.73Fe_1.67Se₂ as seen by muon spin rotation and infrared spectroscopy

Using muon spin rotation and infrared spectroscopy, we investigated the recently discovered superconductor K0.73Fe1.67Se₂ with Tc≈32 K. We show that the combined data can be consistently described in terms of a macroscopically phase-segregated state with a matrix of ∼88% volume fraction that is insulating and strongly magnetic and inclusions with an ∼12% volume fraction, which are metallic, superconducting, and nonmagnetic. The electronic properties of the latter, in terms of the normal state plasma frequency and the superconducting condensate density, appear to be similar as in other iron selenide or arsenide superconductors

Evolutionary distances in the twilight zone -- a rational kernel approach

Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets.Comment: to appear in PLoS ON

N-Linked Glycosylation on Anthrax Toxin Receptor 1 Is Essential for Seneca Valley Virus Infection

Seneca Valley virus (SVV) is a picornavirus with potency in selectively infecting and lysing cancerous cells. The cellular receptor for SVV mediating the selective tropism for tumors is anthrax toxin receptor 1 (ANTXR1), a type I transmembrane protein expressed in tumors. Similar to other mammalian receptors, ANTXR1 has been shown to harbor N-linked glycosylation sites in its extracellular vWA domain. However, the exact role of ANTXR1 glycosylation on SVV attachment and cellular entry was unknown. Here we show that N-linked glycosylation in the ANTXR1 vWA domain is necessary for SVV attachment and entry. In our study, tandem mass spectrometry analysis of recombinant ANTXR1-Fc revealed the presence of complex glycans at N166, N184 in the vWA domain, and N81 in the Fc domain. Symmetry-expanded cryo-EM reconstruction of SVV-ANTXR1-Fc further validated the presence of N166 and N184 in the vWA domain. Cell blocking, co-immunoprecipitation, and plaque formation assays confirmed that deglycosylation of ANTXR1 prevents SVV attachment and subsequent entry. Overall, our results identified N-glycosylation in ANTXR1 as a necessary post-translational modification for establishing stable interactions with SVV. We anticipate our findings will aid in selecting patients for future cancer therapeutics, where screening for both ANTXR1 and its glycosylation could lead to an improved outcome from SVV therapy

Coordinated optimization of visual cortical maps (I) Symmetry-based analysis

In the primary visual cortex of primates and carnivores, functional architecture can be characterized by maps of various stimulus features such as orientation preference (OP), ocular dominance (OD), and spatial frequency. It is a long-standing question in theoretical neuroscience whether the observed maps should be interpreted as optima of a specific energy functional that summarizes the design principles of cortical functional architecture. A rigorous evaluation of this optimization hypothesis is particularly demanded by recent evidence that the functional architecture of OP columns precisely follows species invariant quantitative laws. Because it would be desirable to infer the form of such an optimization principle from the biological data, the optimization approach to explain cortical functional architecture raises the following questions: i) What are the genuine ground states of candidate energy functionals and how can they be calculated with precision and rigor? ii) How do differences in candidate optimization principles impact on the predicted map structure and conversely what can be learned about an hypothetical underlying optimization principle from observations on map structure? iii) Is there a way to analyze the coordinated organization of cortical maps predicted by optimization principles in general? To answer these questions we developed a general dynamical systems approach to the combined optimization of visual cortical maps of OP and another scalar feature such as OD or spatial frequency preference.Comment: 90 pages, 16 figure

Resting-state gamma-band power alterations in schizophrenia reveal E/I-balance abnormalities across illness-stages

We examined alterations in E/I-balance in schizophrenia (ScZ) through measurements of resting-state gamma-band activity in participants meeting clinical high-risk (CHR) criteria (n = 88), 21 first episode (FEP) patients and 34 chronic ScZ-patients. Furthermore, MRS-data were obtained in CHR-participants and matched controls. Magnetoencephalographic (MEG) resting-state activity was examined at source level and MEG-data were correlated with neuropsychological scores and clinical symptoms. CHR-participants were characterized by increased 64–90 Hz power. In contrast, FEP- and ScZ-patients showed aberrant spectral power at both low- and high gamma-band frequencies. MRS-data showed a shift in E/I-balance toward increased excitation in CHR-participants, which correlated with increased occipital gamma-band power. Finally, neuropsychological deficits and clinical symptoms in FEP and ScZ-patients were correlated with reduced gamma band-activity, while elevated psychotic symptoms in the CHR group showed the opposite relationship. The current study suggests that resting-state gamma-band power and altered Glx/GABA ratio indicate changes in E/I-balance parameters across illness stages in ScZ

Self-organization and the selection of pinwheel density in visual cortical development

Self-organization of neural circuitry is an appealing framework for understanding cortical development, yet its applicability remains unconfirmed. Models for the self-organization of neural circuits have been proposed, but experimentally testable predictions of these models have been less clear. The visual cortex contains a large number of topological point defects, called pinwheels, which are detectable in experiments and therefore in principle well suited for testing predictions of self-organization empirically. Here, we analytically calculate the density of pinwheels predicted by a pattern formation model of visual cortical development. An important factor controlling the density of pinwheels in this model appears to be the presence of non-local long-range interactions, a property which distinguishes cortical circuits from many nonliving systems in which self-organization has been studied. We show that in the limit where the range of these interactions is infinite, the average pinwheel density converges to $\pi$. Moreover, an average pinwheel density close to this value is robustly selected even for intermediate interaction ranges, a regime arguably covering interaction-ranges in a wide range of different species. In conclusion, our paper provides the first direct theoretical demonstration and analysis of pinwheel density selection in models of cortical self-organization and suggests to quantitatively probe this type of prediction in future high-precision experiments.Comment: 22 pages, 3 figure

Glycaemic control and antidiabetic therapy in patients with diabetes mellitus and chronic kidney disease - cross-sectional data from the German Chronic Kidney Disease (GCKD) cohort

Background: Diabetes mellitus (DM) is the leading cause of end-stage renal disease. Little is known about practice patterns of anti-diabetic therapy in the presence of chronic kidney disease (CKD) and correlates with glycaemic control. We therefore aimed to analyze current antidiabetic treatment and correlates of metabolic control in a large contemporary prospective cohort of patients with diabetes and CKD. Methods: The German Chronic Kidney Disease (GCKD) study enrolled 5217 patients aged 18-74 years with an estimated glomerular filtration rate (eGFR) between 30-60 mL/min/1.73 m(2) or proteinuria >0.5 g/d. The use of diet prescription, oral anti-diabetic medication, and insulin was assessed at baseline. HbA1c, measured centrally, was the main outcome measure. Results: At baseline, DM was present in 1842 patients (35 %) and the median HbA1C was 7.0 % (25th-75th percentile: 6.8-7.9 %), equalling 53 mmol/mol (51, 63);24.2 % of patients received dietary treatment only, 25.5 % oral antidiabetic drugs but not insulin, 8.4 % oral antidiabetic drugs with insulin, and 41.8 % insulin alone. Metformin was used by 18.8 %. Factors associated with an HbA1C level >7.0 % (53 mmol/mol) were higher BMI (OR = 1.04 per increase of 1 kg/m(2), 95 % CI 1.02-1.06), hemoglobin (OR = 1.11 per increase of 1 g/dL, 95 % CI 1.04-1.18), treatment with insulin alone (OR = 5.63, 95 % CI 4.26-7.45) or in combination with oral antidiabetic agents (OR = 4.23, 95 % CI 2.77-6.46) but not monotherapy with metformin, DPP-4 inhibitors, or glinides. Conclusions: Within the GCKD cohort of patients with CKD stage 3 or overt proteinuria, antidiabetic treatment patterns were highly variable with a remarkably high proportion of more than 50 % receiving insulin-based therapies. Metabolic control was overall satisfactory, but insulin use was associated with higher HbA1C levels