Use of plant epidermis for determination of macrophytes consumed by Distichodus rostratus Günther, 1864 (Pisces : Distichodontidae), of Taabo artificial lake (Basin of Bandama, Côte d’Ivoire).

Fish constitutes one of the principal sources of proteins in the majority of African countries such as Côte d'Ivoire. However, its production is subjected to various constraints primarily of nutritional nature. This study was initiated to determine the plant base diet of local fish Distichodus rostratus for its valorisation in aquaculture. The micro-histological method was applied to the stomach contents and aquatic plants inventoried in Ahondo (Taabo Lake) in order to determine floristic composition of consumed food by D. rostratus. After treatment in sodium hypochlorite, the epidermis of plants were observed using an optic microscope and compared. The results revealed that the plant species consumed by this Fish species were, essentially, Ipomoea aquatica, Echinochloa pyramidalis, Polygonum senegalense and Pycreus macrostachys.Keywords : Distichodus rostratus, diet, epidermis, Aquatic plants, Macrophytis

Contamination des basidiomycètes (Volvariella volvacea et Termitomyces spp) des marchés abidjanais par le plomb, le cadmium, le mercure et le zinc

Le monitoring des éléments traces métalliques (ETM) de l’environnement et des réseaux trophiques a considérablement gagné du terrain durant ces dernières décennies afin de prévenir les problèmes environnementaux et de santé publique. Cette étude s’inscrit dans ce contexte de monitoring et entend évaluer le niveau de contamination de Volvariella volvacea, Termitomyces robustus et Termitomyces letestui par le plomb, le cadmium, le mercure et le zinc. Le dosage des ETM s’effectué par spectrométrie d’absorption atomique sur 77 échantillons de champignon issus des marchés abidjanais. La teneur minimale du plomb, du cadmium et du mercure est 0,01 ± 0,01 mg/kg et celle du zinc est 0,001± 0,001 mg/kg. La teneur maximale du plomb est 1,11 ± 0,01 mg/kg et a été détectée chez Termitomyces letestui. La plus grande teneur du cadmium est 0,52 ± 0,02 mg/kg et a été détectée chez Termitomyces robustus. Les teneurs maximales du mercure et du zinc sont respectivement 0,85 ± 0,04 mg/kg chez Termitomyces letestui et 0,07 ± 0,03 mg/kg chez Termitomyces robustus. Les teneurs moyennes métalliques oscillent entre 0,003 ± 0,001 mg/kg (zinc) et 0,30 ± 0,05 mg/kg (plomb). Les teneurs moyennes métalliques de ces champignons sont conformes aux standards (CE) no1881/2006 de l’Union Européenne.Mots clés : Elément trace métallique, carpophore, bioaccumulation

A Rare third ventricle solitary tuberculoma

The localization of the tuberculoma at the third ventricle is rare. The authors report a case of third ventricle solitary Tuberculoma which has occurred in a 10 year old patient and revealed by a syndrome of intracranial hypertension without tuberculosis stigma. This lesion appears clinically and radiologically as a primary brain tumor. A total removal using a subchoroidal approach to the third ventricle has been performed. Histological examination showed a tuberculous like granuloma. An adjuvant antituberculous chemotherapy  practiced for 6 months brought the complete cure. The authors insist on the diagnostic and therapeutic difficulties in front of a third ventricle solitary  tuberculoma

HI-Tree: Mining High Influence Patterns Using External and Internal Utility Values

We propose an efficient algorithm, called HI-Tree, for mining high influence patterns for an incremental dataset. In traditional pattern mining, one would find the complete set of patterns and then apply a post-pruning step to it. The size of the complete mining results is typically prohibitively large, despite the fact that only a small percentage of high utility patterns are interesting. Thus it is inefficient to wait for the mining algorithm to complete and then apply feature selection to post-process the large number of resulting patterns. Instead of generating the complete set of frequent patterns we are able to directly mine patterns with high utility values in an incremental manner. In this paper we propose a novel utility measure called an influence factor using the concepts of external utility and internal utility of an item. The influence factor for an item takes into consideration its connectivity with its neighborhood as well as its importance within a transaction. The measure is especially useful in problem domains utilizing network or interaction characteristics amongst items such as in a social network or web click-stream data. We compared our technique against state of the art incremental mining techniques and show that our technique has better rule generation and runtime performance

Broadband random optoelectronic oscillator

[EN] Random scattering of light in transmission media has attracted a great deal of attention in the field of photonics over the past few decades. An optoelectronic oscillator (OEO) is a microwave photonic system offering unbeatable features for the generation of microwave oscillations with ultra-low phase noise. Here, we combine the unique features of random scattering and OEO technologies by proposing an OEO structure based on random distributed feedback. Thanks to the random distribution of Rayleigh scattering caused by inhomogeneities within the glass structure of the fiber, we demonstrate the generation of ultra-wideband (up to 40¿GHz from DC) random microwave signals in an open cavity OEO. The generated signals enjoy random characteristics, and their frequencies are not limited by a fixed cavity length figure. The proposed device has potential in many fields such as random bit generation, radar systems, electronic interference and countermeasures, and telecommunications.Thanks N. Shi and Y. Yang for comments and discussion. This work was supported by the National Key Research and Development Program of China under 2018YFB2201902 and the National Natural Science Foundation of China under 61925505. This work was also partly supported by the National Key Research and Development Program of China under 2018YFB2201901, 2018YFB2201903, and the National Natural Science Foundation of China under 61535012 and 61705217.Ge, Z.; Hao, T.; Capmany Francoy, J.; Li, W.; Zhu, N.; Li, M. (2020). Broadband random optoelectronic oscillator. Nature Communications. 11(1):1-8. https://doi.org/10.1038/s41467-020-19596-xS18111Feng, S., Kane, C., Lee, P. A. & Stone, A. D. Correlations and fluctuations of coherent wave transmission through disordered media. Phys. Rev. Lett. 61, 834 (1988).Wiersma, D. S. & Cavalieri, S. Light emission: a temperature-tunable random laser. Nature 414, 708 (2001).Wiersma, D. S. The physics and applications of random lasers. Nat. Phys. 4, 359 (2008).Turitsyn, S. K. et al. Random distributed feedback fibre laser. Nat. Photonics 4, 231–235 (2010).Babin, S. A., El-Taher, A. E., Harper, P., Podivilov, E. V. & Turitsyn, S. K. Tunable random fiber laser. Phys. Rev. A 84, 021805 (2011).Turitsyn, S. K. et al. Random distributed feedback fibre lasers. Phys. Rep. 542, 133–193 (2014).Barnoski, M., Rourke, M., Jensen, S. M. & Melville, R. T. Optical time domain reflectometer. Appl. Opt. 16, 2375–2379 (1977).Yao, X. S. & Maleki, L. Optoelectronic microwave oscillator. JOSA B 13, 1725–1735 (1996).Maleki, L. Sources: the optoelectronic oscillator. Nat. Photonics 5, 728 (2011).Yao, X. S. & Maleki, L. Multiloop optoelectronic oscillator. IEEE J. Quantum Electron 36, 79–84 (2000).Hao, T. et al. Breaking the limitation of mode building time in an optoelectronic oscillator. Nat. Commun. 9, 1839 (2018).Zhang, W. & Yao, J. Silicon photonic integrated optoelectronic oscillator for frequency-tunable microwave generation. J. Lightwave Technol. 36, 4655–4663 (2018).Hao, T. et al. Toward Monolithic Integration of OEOs: from systems to chips. J. Lightwave Technol. 36, 4565–4582 (2018).Zhang, J. & Yao, J. Parity-time–symmetric optoelectronic oscillator. Sci. Adv. 4, eaar6782 (2018).Liu, Y. et al. Observation of parity-time symmetry in microwave photonics. Light Sci. Appl. 7, 38 (2018).Nakazawa, M. Rayleigh backscattering theory for single-mode optical fibers. JOSA 73, 1175–1180 (1983).Hartog, A. & Gold, M. On the theory of backscattering in single-mode optical fibers. J. Lightwave Technol. 2, 76–82 (1984).Eickhoff, W., & Ulrich, R. Statistics of backscattering in single-mode fiber. In Optical Fiber Communication Conference. Optical Society of America (1981).Alekseev, A. E., Tezadov, Y. A. & Potapov, V. T. Statistical properties of backscattered semiconductor laser radiation with different degrees of coherence. Quantum Electron 42, 76–81 (2012).Gysel, P. & Staubli, R. K. Statistical properties of Rayleigh backscattering in single-mode fibers. J. Lightwave Technol. 8, 561–567 (1990).Staubli, R. K. & Gysel, P. Statistical properties of single-mode fiber rayleigh backscattered intensity and resulting detector current. IEEE Trans. Commun. 40, 1091–1097 (1992).Levy, E. C., Horowitz, M. & Menyuk, C. R. Modeling optoelectronic oscillators. JOSA B 26, 148–159 (2009).Yariv, A. Introduction to Optical Electronics 2nd edn. (Holt, Rinehart and Winston, New York, 1976).Aoki, Y., Tajima, K. & Mito, I. Input power limits of single-mode optical fibers due to stimulated Brillouin scattering in optical communication systems. J. Lightwave Technol. 6, 710–719 (1988).Song, H. J., Shimizu, N., Kukutsu, N., Nagatsuma, T. & Kado, Y. Microwave photonic noise source from microwave to sub-terahertz wave bands and its applications to noise characterization. IEEE Trans. Microw. Theory Tech. 56, 2989–2997 (2008).Chembo, Y. K., et al. Optoelectronic oscillators with time-delayed feedback. Rev. Mod. Phys. 91, 035006 (2019).Callan, K. E. et al. Broadband chaos generated by an optoelectronic oscillator. Phys. Rev. Lett. 104, 113901 (2010).Lavrov, R. et al. Electro-optic delay oscillator with nonlocal nonlinearity: Optical phase dynamics, chaos, and synchronization. Phys. Rev. E. 80, 026207 (2009).Wolf, A., Swift, J. B., Swinney, H. L. & Vastano, J. A. Determining Lyapunov exponents from a time series. Phys. D. 16, 285–317 (1985).Grassberger, P. & Procaccia, I. Characterization of strange attractors. Phys. Rev. Lett. 50, 346 (1983).Grassberger, P. & Procaccia, I. Measuring the strangeness of strange attractors. Phys. D. 9, 189–208 (1983).Romeira, B. et al. Broadband chaotic signals and breather oscillations in an optoelectronic oscillator incorporating a microwave photonic filter. J. Lightwave Technol. 32, 3933–3942 (2014)

Serotonin and corticosterone rhythms in mice exposed to cigarette smoke and in patients with COPD:implication for COPD-associated neuropathogenesis

The circadian timing system controls daily rhythms of physiology and behavior, and disruption of clock function can trigger stressful life events. Daily exposure to cigarette smoke (CS) can lead to alteration in diverse biological and physiological processes. Smoking is associated with mood disorders, including depression and anxiety. Patients with chronic obstructive pulmonary disease (COPD) have abnormal circadian rhythms, reflected by daily changes in respiratory symptoms and lung function. Corticosterone (CORT) is an adrenal steroid that plays a considerable role in stress and anti-inflammatory responses. Serotonin (5-hydroxytryptamine; 5HT) is a neurohormone, which plays a role in sleep/wake regulation and affective disorders. Secretion of stress hormones (CORT and 5HT) is under the control of the circadian clock in the suprachiasmatic nucleus. Since smoking is a contributing factor in the development of COPD, we hypothesize that CS can affect circadian rhythms of CORT and 5HT secretion leading to sleep and mood disorders in smokers and patients with COPD. We measured the daily rhythms of plasma CORT and 5HT in mice following acute (3 d), sub-chronic (10 d) or chronic (6 mo) CS exposure and in plasma from non-smokers, smokers and patients with COPD. Acute and chronic CS exposure affected both the timing (peak phase) and amplitude of the daily rhythm of plasma CORT and 5HT in mice. Acute CS appeared to have subtle time-dependent effects on CORT levels but more pronounced effects on 5HT. As compared with CORT, plasma 5HT was slightly elevated in smokers but was reduced in patients with COPD. Thus, the effects of CS on plasma 5HT were consistent between mice and patients with COPD. Together, these data reveal a significant impact of CS exposure on rhythms of stress hormone secretion and subsequent detrimental effects on cognitive function, depression-like behavior, mood/anxiety and sleep quality in smokers and patients with COPD

Physiology and cell biology of acupuncture observed in calcium signaling activated by acoustic shear wave

This article presents a novel model of acupuncture physiology based on cellular calcium activation by an acoustic shear wave (ASW) generated by the mechanical movement of the needle. An acupuncture needle was driven by a piezoelectric transducer at 100 Hz or below, and the ASW in human calf was imaged by magnetic resonance elastography. At the cell level, the ASW activated intracellular Ca 2+ transients and oscillations in fibroblasts and endothelial, ventricular myocytes and neuronal PC-12 cells along with frequency-amplitude tuning and memory capabilities. Monitoring in vivo mammalian experiments with ASW, enhancement of endorphin in blood plasma and blocking by Gd 3+ were observed; and increased Ca 2+ fluorescence in mouse hind leg muscle was imaged by two-photon microscopy. In contrast with traditional acupuncture models, the signal source is derived from the total acoustic energy. ASW signaling makes use of the anisotropy of elasticity of tissues as its waveguides for transmission and that cell activation is not based on the nervous system. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

Ferritins: furnishing proteins with iron

Ferritins are a superfamily of iron oxidation, storage and mineralization proteins found throughout the animal, plant, and microbial kingdoms. The majority of ferritins consist of 24 subunits that individually fold into 4-α-helix bundles and assemble in a highly symmetric manner to form an approximately spherical protein coat around a central cavity into which an iron-containing mineral can be formed. Channels through the coat at inter-subunit contact points facilitate passage of iron ions to and from the central cavity, and intrasubunit catalytic sites, called ferroxidase centers, drive Fe2+ oxidation and O2 reduction. Though the different members of the superfamily share a common structure, there is often little amino acid sequence identity between them. Even where there is a high degree of sequence identity between two ferritins there can be major differences in how the proteins handle iron. In this review we describe some of the important structural features of ferritins and their mineralized iron cores and examine in detail how three selected ferritins oxidise Fe2+ in order to explore the mechanistic variations that exist amongst ferritins. We suggest that the mechanistic differences reflect differing evolutionary pressures on amino acid sequences, and that these differing pressures are a consequence of different primary functions for different ferritins

Building nonparametric nn-body force fields using Gaussian process regression

Constructing a classical potential suited to simulate a given atomic system is a remarkably difficult task. This chapter presents a framework under which this problem can be tackled, based on the Bayesian construction of nonparametric force fields of a given order using Gaussian process (GP) priors. The formalism of GP regression is first reviewed, particularly in relation to its application in learning local atomic energies and forces. For accurate regression it is fundamental to incorporate prior knowledge into the GP kernel function. To this end, this chapter details how properties of smoothness, invariance and interaction order of a force field can be encoded into corresponding kernel properties. A range of kernels is then proposed, possessing all the required properties and an adjustable parameter $n$ governing the interaction order modelled. The order $n$ best suited to describe a given system can be found automatically within the Bayesian framework by maximisation of the marginal likelihood. The procedure is first tested on a toy model of known interaction and later applied to two real materials described at the DFT level of accuracy. The models automatically selected for the two materials were found to be in agreement with physical intuition. More in general, it was found that lower order (simpler) models should be chosen when the data are not sufficient to resolve more complex interactions. Low $n$ GPs can be further sped up by orders of magnitude by constructing the corresponding tabulated force field, here named "MFF".Comment: 31 pages, 11 figures, book chapte