An analysis of waves underlying grid cell firing in the medial enthorinal cortex

Layer II stellate cells in the medial enthorinal cortex (MEC) express hyperpolarisation-activated cyclic-nucleotide-gated (HCN) channels that allow for rebound spiking via an I_h current in response to hyperpolarising synaptic input. A computational modelling study by Hasselmo [2013 Neuronal rebound spiking, resonance frequency and theta cycle skipping may contribute to grid cell firing in medial entorhinal cortex. Phil. Trans. R. Soc. B 369: 20120523] showed that an inhibitory network of such cells can support periodic travelling waves with a period that is controlled by the dynamics of the I_h current. Hasselmo has suggested that these waves can underlie the generation of grid cells, and that the known difference in I_h resonance frequency along the dorsal to ventral axis can explain the observed size and spacing between grid cell firing fields. Here we develop a biophysical spiking model within a framework that allows for analytical tractability. We combine the simplicity of integrate-and-fire neurons with a piecewise linear caricature of the gating dynamics for HCN channels to develop a spiking neural field model of MEC. Using techniques primarily drawn from the field of nonsmooth dynamical systems we show how to construct periodic travelling waves, and in particular the dispersion curve that determines how wave speed varies as a function of period. This exhibits a wide range of long wavelength solutions, reinforcing the idea that rebound spiking is a candidate mechanism for generating grid cell firing patterns. Importantly we develop a wave stability analysis to show how the maximum allowed period is controlled by the dynamical properties of the I_h current. Our theoretical work is validated by numerical simulations of the spiking model in both one and two dimensions

Diabetes mellitus, maternal adiposity, and insulin-dependent gestational diabetes are associated with COVID-19 in pregnancy: the INTERCOVID study

BACKGROUND: Among nonpregnant individuals, diabetes mellitus and high body mass index increase the risk of COVID-19 and its severity.OBJECTIVE: This study aimed to determine whether diabetes mellitus and high body mass index are risk factors for COVID-19 in pregnancy and whether gestational diabetes mellitus is associated with COVID-19 diagnosis.STUDY DESIGN: INTERCOVID was a multinational study conducted between March 2020 and February 2021 in 43 institutions from 18 countries, enrolling 2184 pregnant women aged >= 18 years; a total of 2071 women were included in the analyses. For each woman diagnosed with COVID-19, 2 nondiagnosed women delivering or initiating antenatal care at the same institution were also enrolled. The main exposures were preexisting diabetes mellitus, high body mass index (overweight or obesity was defined as a body mass index >= 25 kg/m(2)), and gestational diabetes mellitus in pregnancy. The main outcome was a confirmed diagnosis of COVID-19 based on a real-time polymerase chain reaction test, antigen test, antibody test, radiological pulmonary findings, or >= 2 predefined COVID-19 symptoms at any time during pregnancy or delivery. Relationships of exposures and COVID-19 diagnosis were assessed using generalized linear models with a Poisson distribution and log link function, with robust standard errors to account for model misspecification. Furthermore, we conducted sensitivity analyses: (1) restricted to those with a real-time polymerase chain reaction test or an antigen test in the last week of pregnancy, (2) restricted to those with a real-time polymerase chain reaction test or an antigen test during the entire pregnancy, (3) generating values for missing data using multiple imputation, and (4) analyses controlling for month of enrollment. In addition, among women who were diagnosed with COVID-19, we examined whether having gestational diabetes mellitus, diabetes mellitus, or high body mass index increased the risk of having symptomatic vs asymptomatic COVID-19.RESULTS: COVID-19 was associated with preexisting diabetes mellitus (risk ratio, 1.94; 95% confidence interval, 1.55-2.42), overweight or obesity (risk ratio, 1.20; 95% confidence interval, 1.06-1.37), and gestational diabetes mellitus (risk ratio, 1.21; 95% confidence interval, 0.99-1.46). The gestational diabetes mellitus association was specifically among women requiring insulin, whether they were of normal weight (risk ratio, 1.79; 95% confidence interval, 1.06-3.01) or overweight or obese (risk ratio, 1.77; 95% confidence interval, 1.28-2.45). A somewhat stronger association with COVID-19 diagnosis was observed among women with preexisting diabetes mellitus, whether they were of normal weight (risk ratio, 1.93; 95% confidence interval, 1.18-3.17) or overweight or obese (risk ratio, 2.32; 95% confidence interval, 1.82-2.97). When the sample was restricted to those with a real-time polymerase chain reaction test or an antigen test in the week before delivery or during the entire pregnancy, including missing variables using imputation or controlling for month of enrollment, the observed associations were comparable.CONCLUSION: Diabetes mellitus and overweight or obesity were risk factors for COVID-19 diagnosis in pregnancy, and insulin-dependent gestational diabetes mellitus was associated with the disease. Therefore, it is essential that women with these comorbidities are vaccinated

Immunohistochemical localization and mRNA expression of aquaporins in the macula utriculi of patients with Meniere’s disease and acoustic neuroma

Meniere’s disease is nearly invariably associated with endolymphatic hydrops (the net accumulation of water in the inner ear endolymphatic space). Vestibular maculae utriculi were acquired from patients undergoing surgery for Meniere’s disease and acoustic neuroma and from autopsy (subjects with normal hearing and balance). Quantitative immunostaining was conducted with antibodies against aquaporins (AQPs) 1, 4, and 6, Na+K+ATPase, Na+K+2Cl co-transporter (NKCC1), and α-syntrophin. mRNA was extracted from the surgically acquired utricles from subjects with Meniere’s disease and acoustic neuroma to conduct quantitative real-time reverse transcription with polymerase chain reaction for AQP1, AQP4, and AQP6. AQP1 immunoreactivity (−IR) was located in blood vessels and fibrocytes in the underlying stroma, without any apparent alteration in Meniere’s specimens when compared with acoustic neuroma and autopsy specimens. AQP4-IR localized to the epithelial basolateral supporting cells in Meniere’s disease, acoustic neuroma, and autopsy. In specimens from subjects with Meniere’s disease, AQP4-IR was significantly decreased compared with autopsy and acoustic neuroma specimens. AQP6-IR occurred in the sub-apical vestibular supporting cells in acoustic neuroma and autopsy samples. However, in Meniere’s disease specimens, AQP6-IR was significantly increased and diffusely redistributed throughout the supporting cell cytoplasm. Na+K+ATPase, NKCC1, and α-syntrophin were expressed within sensory epithelia and were unaltered in Meniere’s disease specimens. Expression of AQP1, AQP4, or AQP6 mRNA did not differ in vestibular endorgans from patients with Meniere’s disease. Changes in AQP4 (decreased) and AQP6 (increased) expression in Meniere’s disease specimens suggest that the supporting cell might be a cellular target

Mutation analysis of SDHB and SDHC: novel germline mutations in sporadic head and neck paraganglioma and familial paraganglioma and/or pheochromocytoma

BACKGROUND: Germline mutations of the SDHD, SDHB and SDHC genes, encoding three of the four subunits of succinate dehydrogenase, are a major cause of hereditary paraganglioma and pheochromocytoma, and demonstrate that these genes are classic tumor suppressors. Succinate dehydrogenase is a heterotetrameric protein complex and a component of both the Krebs cycle and the mitochondrial respiratory chain (succinate:ubiquinone oxidoreductase or complex II). METHODS: Using conformation sensitive gel electrophoresis (CSGE) and direct DNA sequencing to analyse genomic DNA from peripheral blood lymphocytes, here we describe the mutation analysis of the SDHB and SDHC genes in 37 patients with sporadic (i.e. no known family history) head and neck paraganglioma and five pheochromocytoma and/or paraganglioma families. RESULTS: Two sporadic patients were found to have a SDHB splice site mutation in intron 4, c.423+1G>A, which produces a mis-spliced transcript with a 54 nucleotide deletion, resulting in an 18 amino acid in-frame deletion. A third patient was found to carry the c.214C>T (p.Arg72Cys) missense mutation in exon 4 of SDHC, which is situated in a highly conserved protein motif that constitutes the quinone-binding site of the succinate: ubiquinone oxidoreductase (SQR) complex in E. coli. Together with our previous results, we found 27 germline mutations of SDH genes in 95 cases (28%) of sporadic head and neck paraganglioma. In addition all index patients of five families showing hereditary pheochromocytoma-paraganglioma were found to carry germline mutations of SDHB: four of which were novel, c.343C>T (p.Arg115X), c.141G>A (p.Trp47X), c.281G>A (p.Arg94Lys), and c.653G>C (p.Trp218Ser), and one reported previously, c.136C>T, p.Arg46X. CONCLUSION: In conclusion, these data indicate that germline mutations of SDHB and SDHC play a minor role in sporadic head and neck paraganglioma and further underline the importance of germline SDHB mutations in cases of familial pheochromocytoma-paraganglioma

Grid Cells, Place Cells, and Geodesic Generalization for Spatial Reinforcement Learning

Reinforcement learning (RL) provides an influential characterization of the brain's mechanisms for learning to make advantageous choices. An important problem, though, is how complex tasks can be represented in a way that enables efficient learning. We consider this problem through the lens of spatial navigation, examining how two of the brain's location representations—hippocampal place cells and entorhinal grid cells—are adapted to serve as basis functions for approximating value over space for RL. Although much previous work has focused on these systems' roles in combining upstream sensory cues to track location, revisiting these representations with a focus on how they support this downstream decision function offers complementary insights into their characteristics. Rather than localization, the key problem in learning is generalization between past and present situations, which may not match perfectly. Accordingly, although neural populations collectively offer a precise representation of position, our simulations of navigational tasks verify the suggestion that RL gains efficiency from the more diffuse tuning of individual neurons, which allows learning about rewards to generalize over longer distances given fewer training experiences. However, work on generalization in RL suggests the underlying representation should respect the environment's layout. In particular, although it is often assumed that neurons track location in Euclidean coordinates (that a place cell's activity declines “as the crow flies” away from its peak), the relevant metric for value is geodesic: the distance along a path, around any obstacles. We formalize this intuition and present simulations showing how Euclidean, but not geodesic, representations can interfere with RL by generalizing inappropriately across barriers. Our proposal that place and grid responses should be modulated by geodesic distances suggests novel predictions about how obstacles should affect spatial firing fields, which provides a new viewpoint on data concerning both spatial codes

Disrupting Circadian Homeostasis of Sympathetic Signaling Promotes Tumor Development in Mice

and why disruption of circadian rhythm may lead to tumorigenesis. oncogenic potential, leading to tumor development in the same organ systems in wild-type and circadian gene-mutant mice. is a clock-controlled physiological function. The central circadian clock paces extracellular mitogenic signals that drive peripheral clock-controlled expression of key cell cycle and tumor suppressor genes to generate a circadian rhythm in cell proliferation. Frequent disruption of circadian rhythm is an important tumor promoting factor

Characterization of a Drosophila Alzheimer's Disease Model: Pharmacological Rescue of Cognitive Defects

Transgenic models of Alzheimer's disease (AD) have made significant contributions to our understanding of AD pathogenesis, and are useful tools in the development of potential therapeutics. The fruit fly, Drosophila melanogaster, provides a genetically tractable, powerful system to study the biochemical, genetic, environmental, and behavioral aspects of complex human diseases, including AD. In an effort to model AD, we over-expressed human APP and BACE genes in the Drosophila central nervous system. Biochemical, neuroanatomical, and behavioral analyses indicate that these flies exhibit aspects of clinical AD neuropathology and symptomology. These include the generation of Aβ40 and Aβ42, the presence of amyloid aggregates, dramatic neuroanatomical changes, defects in motor reflex behavior, and defects in memory. In addition, these flies exhibit external morphological abnormalities. Treatment with a γ-secretase inhibitor suppressed these phenotypes. Further, all of these phenotypes are present within the first few days of adult fly life. Taken together these data demonstrate that this transgenic AD model can serve as a powerful tool for the identification of AD therapeutic interventions