Contribution of the d-Serine-Dependent Pathway to the Cellular Mechanisms Underlying Cognitive Aging

An association between age-related memory impairments and changes in functional plasticity in the aging brain has been under intense study within the last decade. In this article, we show that an impaired activation of the strychnine-insensitive glycine site of N-methyl-d-aspartate receptors (NMDA-R) by its agonist d-serine contributes to deficits of synaptic plasticity in the hippocampus of memory-impaired aged rats. Supplementation with exogenous d-serine prevents the age-related deficits of isolated NMDA-R-dependent synaptic potentials as well as those of theta-burst-induced long-term potentiation and synaptic depotentiation. Endogenous levels of d-serine are reduced in the hippocampus with aging, that correlates with a weaker expression of serine racemase synthesizing the amino acid. On the contrary, the affinity of d-serine binding to NMDA-R is not affected by aging. These results point to a critical role for the d-serine-dependent pathway in the functional alterations of the brain underlying memory impairment and provide key information in the search for new therapeutic strategies for the treatment of memory deficits in the elderly

Glial D-Serine Gates NMDA Receptors at Excitatory Synapses in Prefrontal Cortex.

N-methyl-D-aspartate receptors (NMDARs) subserve numerous neurophysiological and neuropathological processes in the cerebral cortex. Their activation requires the binding of glutamate and also of a coagonist. Whereas glycine and D-serine (D-ser) are candidates for such a role at central synapses, the nature of the coagonist in cerebral cortex remains unknown. We first show that the glycine-binding site of NMDARs is not saturated in acute slices preparations of medial prefrontal cortex (mPFC). Using enzymes that selectively degrade either D-ser or glycine, we demonstrate that under the present conditions, D-ser is the principle endogenous coagonist of synaptic NMDARs at mature excitatory synapses in layers V/VI of mPFC where it is essential for long-term potentiation (LTP) induction. Furthermore, blocking the activity of glia with the metabolic inhibitor, fluoroacetate, impairs NMDAR-mediated synaptic transmission and prevents LTP induction by reducing the extracellular levels of D-serine. Such deficits can be restored by exogenous D-ser, indicating that the D-amino acid mainly originates from glia in the mPFC, as further confirmed by double-immunostaining studies for D-ser and anti-glial fibrillary acidic protein. Our findings suggest that D-ser modulates neuronal networks in the cerebral cortex by gating the activity of NMDARs and that altering its levels is relevant to the induction and potentially treatment of psychiatric and neurological disorders

Detecting glaucoma from multi-modal data using probabilistic deep learning

Objective: To assess the accuracy of probabilistic deep learning models to discriminate normal eyes and eyes with glaucoma from fundus photographs and visual fields. Design: Algorithm development for discriminating normal and glaucoma eyes using data from multicenter, cross-sectional, case-control study. Subjects and participants: Fundus photograph and visual field data from 1,655 eyes of 929 normal and glaucoma subjects to develop and test deep learning models and an independent group of 196 eyes of 98 normal and glaucoma patients to validate deep learning models. Main outcome measures: Accuracy and area under the receiver-operating characteristic curve (AUC). Methods: Fundus photographs and OCT images were carefully examined by clinicians to identify glaucomatous optic neuropathy (GON). When GON was detected by the reader, the finding was further evaluated by another clinician. Three probabilistic deep convolutional neural network (CNN) models were developed using 1,655 fundus photographs, 1,655 visual fields, and 1,655 pairs of fundus photographs and visual fields collected from Compass instruments. Deep learning models were trained and tested using 80% of fundus photographs and visual fields for training set and 20% of the data for testing set. Models were further validated using an independent validation dataset. The performance of the probabilistic deep learning model was compared with that of the corresponding deterministic CNN model. Results: The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and combined modalities using development dataset were 0.90 (95% confidence interval: 0.89–0.92), 0.89 (0.88–0.91), and 0.94 (0.92–0.96), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using the independent validation dataset were 0.94 (0.92–0.95), 0.98 (0.98–0.99), and 0.98 (0.98–0.99), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using an early glaucoma subset were 0.90 (0.88,0.91), 0.74 (0.73,0.75), 0.91 (0.89,0.93), respectively. Eyes that were misclassified had significantly higher uncertainty in likelihood of diagnosis compared to eyes that were classified correctly. The uncertainty level of the correctly classified eyes is much lower in the combined model compared to the model based on visual fields only. The AUCs of the deterministic CNN model using fundus images, visual field, and combined modalities based on the development dataset were 0.87 (0.85,0.90), 0.88 (0.84,0.91), and 0.91 (0.89,0.94), and the AUCs based on the independent validation dataset were 0.91 (0.89,0.93), 0.97 (0.95,0.99), and 0.97 (0.96,0.99), respectively, while the AUCs based on an early glaucoma subset were 0.88 (0.86,0.91), 0.75 (0.73,0.77), and 0.92 (0.89,0.95), respectively. Conclusion and relevance: Probabilistic deep learning models can detect glaucoma from multi-modal data with high accuracy. Our findings suggest that models based on combined visual field and fundus photograph modalities detects glaucoma with higher accuracy. While probabilistic and deterministic CNN models provided similar performance, probabilistic models generate certainty level of the outcome thus providing another level of confidence in decision making

Antirhea borbonica Aqueous Extract Protects Albumin and Erythrocytes from Glycoxidative Damages

Diabetes constitutes a major health problem associated with severe complications. In hyperglycemic conditions, chronically increased oxidation and glycation of circulating components lead to advanced glycation end-products (AGEs) formation, a key contributor in diabetes complication progression. In line with literature documenting the beneficial properties of herbal teas, this study evaluates the antioxidant/glycant properties of Antirhea borbonica (Ab). Ab aqueous extract effects were tested on human albumin or erythrocytes submitted to methyl glyoxal-mediated glycoxidative damages. By using mass spectrometry, Ab aqueous extracts revealed to be rich in polyphenols. All tested biomarkers of oxidation and glycation, such as AGE, ketoamine, oxidized thiol groups, were decreased in albumin when glycated in the presence of Ab aqueous extract. Ab extract preserve erythrocyte from methylglyoxal (MGO)-induced damages in terms of restored membrane deformability, reduced oxidative stress and eryptosis phenomenon. Antioxidant capacities of Ab extract on erythrocytes were retrieved in vivo in zebrafish previously infused with MGO. These results bring new evidences on the deleterious impacts of glycation on albumin and erythrocyte in diabetes. Furthermore, it reveals antioxidant and antiglycant properties of Ab that could be used for the dietary modulation of oxidative stress and glycation in hyperglycemic situations

Molecular excitation in the Interstellar Medium: recent advances in collisional, radiative and chemical processes

We review the different excitation processes in the interstellar mediumComment: Accepted in Chem. Re

Evidence for ambient dark aqueous SOA formation in the Po Valley, Italy

Laboratory experiments suggest that water-soluble products from the gas-phase oxidation of volatile organic compounds can partition into atmospheric waters where they are further oxidized to form low volatility products, providing an alternative route for oxidation in addition to further oxidation in the gas phase. These products can remain in the particle phase after water evaporation, forming what is termed as aqueous secondary organic aerosol (aqSOA). However, few studies have attempted to observe ambient aqSOA. Therefore, a suite of measurements, including near-real-time WSOC (water-soluble organic carbon), inorganic anions/cations, organic acids, and gas-phase glyoxal, were made during the PEGASOS (Pan-European Gas-AeroSOls-climate interaction Study) 2012 campaign in the Po Valley, Italy, to search for evidence of aqSOA. Our analysis focused on four periods: Period A on 19–21 June, Period B on 30 June and 1–2 July, Period C on 3–5 July, and Period D on 6–7 July to represent the first (Period A) and second (Periods B, C, and D) halves of the study. These periods were picked to cover varying levels of WSOC and aerosol liquid water. In addition, back trajectory analysis suggested all sites sampled similar air masses on a given day. The data collected during both periods were divided into times of increasing relative humidity (RH) and decreasing RH, with the aim of diminishing the influence of dilution and mixing on SOA concentrations and other measured variables. Evidence for local aqSOA formation was only observed during Period A. When this occurred, there was a correlation of WSOC with organic aerosol (R2 = 0.84), aerosol liquid water (R2 = 0.65), RH (R2 = 0.39), and aerosol nitrate (R2 = 0.66). Additionally, this was only observed during times of increasing RH, which coincided with dark conditions. Comparisons of WSOC with oxygenated organic aerosol (OOA) factors, determined from application of positive matrix factorization analysis on the aerosol mass spectrometer observations of the submicron non-refractory organic particle composition, suggested that the WSOC differed in the two halves of the study (Period A WSOC vs. OOA-2 R2 = 0.83 and OOA-4 R2 = 0.04, whereas Period C WSOC vs. OOA-2 R2 = 0.03 and OOA-4 R2 = 0.64). OOA-2 had a high O ∕ C (oxygen ∕ carbon) ratio of 0.77, providing evidence that aqueous processing was occurring during Period A. Key factors of local aqSOA production during Period A appear to include air mass stagnation, which allows aqSOA precursors to accumulate in the region; the formation of substantial local particulate nitrate during the overnight hours, which enhances water uptake by the aerosol; and the presence of significant amounts of ammonia, which may contribute to ammonium nitrate formation and subsequent water uptake and/or play a more direct role in the aqSOA chemistry

Search for muon-neutrino emission from GeV and TeV gamma-ray flaring blazars using five years of data of the ANTARES telescope

The ANTARES telescope is well-suited for detecting astrophysical transient neutrino sources as it can observe a full hemisphere of the sky at all times with a high duty cycle. The background due to atmospheric particles can be drastically reduced, and the point-source sensitivity improved, by selecting a narrow time window around possible neutrino production periods. Blazars, being radio-loud active galactic nuclei with their jets pointing almost directly towards the observer, are particularly attractive potential neutrino point sources, since they are among the most likely sources of the very high-energy cosmic rays. Neutrinos and gamma rays may be produced in hadronic interactions with the surrounding medium. Moreover, blazars generally show high time variability in their light curves at different wavelengths and on various time scales. This paper presents a time-dependent analysis applied to a selection of flaring gamma-ray blazars observed by the FERMI/LAT experiment and by TeV Cherenkov telescopes using five years of ANTARES data taken from 2008 to 2012. The results are compatible with fluctuations of the background. Upper limits on the neutrino fluence have been produced and compared to the measured gamma-ray spectral energy distribution.Comment: 27 pages, 16 figure

The Antares Collaboration : Contributions to the 34th International Cosmic Ray Conference (ICRC 2015, The Hague)

The ANTARES detector, completed in 2008, is the largest neutrino telescope in the Northern hemisphere. Located at a depth of 2.5 km in the Mediterranean Sea, 40 km off the Toulon shore, its main goal is the search for astrophysical high energy neutrinos. In this paper we collect the 21 contributions of the ANTARES collaboration to the 34th International Cosmic Ray Conference (ICRC 2015). The scientific output is very rich and the contributions included in these proceedings cover the main physics results, ranging from steady point sources, diffuse searches, multi-messenger analyses to exotic physics