Sustained Activation of PV+ Interneurons in Core Auditory Cortex Enables Robust Divisive Gain Control for Complex and Naturalistic Stimuli

Sensory cortices must flexibly adapt their operations to internal states and external requirements. Sustained modulation of activity levels in different inhibitory interneuron populations may provide network-level mechanisms for adjustment of sensory cortical processing on behaviorally relevant timescales. However, understanding of the computational roles of inhibitory interneuron modulation has mostly been restricted to effects at short timescales, through the use of phasic optogenetic activation and transient stimuli. Here, we investigated how modulation of inhibitory interneurons affects cortical computation on longer timescales, by using sustained, network-wide optogenetic activation of parvalbumin-positive interneurons (the largest class of cortical inhibitory interneurons) to study modulation of auditory cortical responses to prolonged and naturalistic as well as transient stimuli. We found highly conserved spectral and temporal tuning in auditory cortical neurons, despite a profound reduction in overall network activity. This reduction was predominantly divisive, and consistent across simple, complex, and naturalistic stimuli. A recurrent network model with power-law input–output functions replicated our results. We conclude that modulation of parvalbumin-positive interneurons on timescales typical of sustained neuromodulation may provide a means for robust divisive gain control conserving stimulus representations

Croup and COVID‐19

info:eu-repo/semantics/publishedVersio

Potencial antimicrobiano de extratos de plantas na inibição de leveduras do gênero Candida

The increase in the resistance to antimicrobial drugs in use has attracted the attention of the scientific community, and medicinal plants have been extensively studied as alternative agents for the prevention of infections. The Candida genus yeast can become an opportunistic pathogen causing disease in immunosuppressive hosts. The purpose of this study was to evaluate dichloromethane and methanol extracts from Mentha piperita, Rosmarinus officinalis, Arrabidaea chica, Tabebuia avellanedae, Punica granatum and Syzygium cumini against Candida species through the analysis of Minimum Inhibitory Concentration (MIC). Results presented activity of these extracts against Candida species, especially the methanol extract.Devido ao aumento da resistência aos antimicrobianos em uso, as plantas medicinais têm sido intensamente estudadas como agentes alternativos para a prevenção de doenças e infecções. A levedura do gênero Candida, por ser um patógeno oportunista, tem sua virulência aumentada ao adquirir resistência aos antifúngicos, desencadeando doenças, principalmente em hospedeiros imunossuprimidos. O propósito deste trabalho foi avaliar os extratos diclorometano e metanol das plantas Mentha piperita, Rosmarinus officinalis, Arrabidaea chica, Tabebuia avellanedae, Punica granatum e Syzygium cumini contra linhagens do gênero Candida através dos testes de Concentração Inibitória Mínima (CIM). Os resultados demonstraram atividade dos extratos sobre as espécies de Candida, particularmente o extrato metanol.10651068Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Stellar Coronal and Wind Models: Impact on Exoplanets

Surface magnetism is believed to be the main driver of coronal heating and stellar wind acceleration. Coronae are believed to be formed by plasma confined in closed magnetic coronal loops of the stars, with winds mainly originating in open magnetic field line regions. In this Chapter, we review some basic properties of stellar coronae and winds and present some existing models. In the last part of this Chapter, we discuss the effects of coronal winds on exoplanets.Comment: Chapter published in the "Handbook of Exoplanets", Editors in Chief: Juan Antonio Belmonte and Hans Deeg, Section Editor: Nuccio Lanza. Springer Reference Work

Discrimination of water quality monitoring sites in River Vouga using a mixed-effect state space model

The surface water quality monitoring is an important concern of public organizations due to its relevance to the public health. Statistical methods are taken as consistent and essential tools in the monitoring procedures in order to prevent and identify environmental problems. This work presents the study case of the hydrological basin of the river Vouga, in Portugal. The main goal is discriminate the water monitoring sites using the monthly dissolved oxygen concentration dataset between January 2002 and May 2013. This is achieved through the extraction of trend and seasonal components in a linear mixed-effect state space model. The parameters estimation is performed with both maximum likelihood method and distribution-free estimators in a two-step procedure. The application of the Kalman smoother algorithm allows to obtain predictions of the structural components as trend and seasonality. The water monitoring sites are discriminated through the structural components by a hierarchical agglomerative clustering procedure. This procedure identified different homogenous groups relatively to the trend and seasonality components and some characteristics of the hydrological basin are presented in order to support the results