Dynamics of Sleep-Wake Transitions During Sleep

We study the dynamics of the awakening during the night for healthy subjects and find that the wake and the sleep periods exhibit completely different behavior: the durations of wake periods are characterized by a scale-free power-law distribution, while the durations of sleep periods have an exponential distribution with a characteristic time scale. We find that the characteristic time scale of sleep periods changes throughout the night. In contrast, there is no measurable variation in the power-law behavior for the durations of wake periods. We develop a stochastic model which agrees with the data and suggests that the difference in the dynamics of sleep and wake states arises from the constraints on the number of microstates in the sleep-wake system.Comment: Final form with some small corrections. To be published in Europhysics Letters, vol. 57, issue no. 5, 1 March 2002, pp. 625-63

Gut barrier-microbiota imbalances in early life lead to higher sensitivity to inflammation in a murine model of C-section delivery

Background Most interactions between the host and its microbiota occur at the gut barrier, and primary colonizers are essential in the gut barrier maturation in the early life. The mother–ofspring transmission of microorganisms is the most important factor infuencing microbial colonization in mammals, and C‑section delivery (CSD) is an impor‑ tant disruptive factor of this transfer. Recently, the deregulation of symbiotic host‑microbe interactions in early life has been shown to alter the maturation of the immune system, predisposing the host to gut barrier dysfunction and infammation. The main goal of this study is to decipher the role of the early‑life gut microbiota‑barrier alterations and its links with later‑life risks of intestinal infammation in a murine model of CSD. Results The higher sensitivity to chemically induced infammation in CSD mice is related to excessive exposure to a too diverse microbiota too early in life. This early microbial stimulus has short‑term consequences on the host homeo‑ stasis. It switches the pup’s immune response to an infammatory context and alters the epithelium structure and the mucus‑producing cells, disrupting gut homeostasis. This presence of a too diverse microbiota in the very early life involves a disproportionate short‑chain fatty acids ratio and an excessive antigen exposure across the vulnerable gut barrier in the frst days of life, before the gut closure. Besides, as shown by microbiota transfer experiments, the microbiota is causal in the high sensitivity of CSD mice to chemical‑induced colitis and in most of the phenotypical parameters found altered in early life. Finally, supplementation with lactobacilli, the main bacterial group impacted by CSD in mice, reverts the higher sensitivity to infammation in ex‑germ‑free mice colonized by CSD pups’ microbiota. Conclusions Early‑life gut microbiota‑host crosstalk alterations related to CSD could be the linchpin behind the phe‑ notypic efects that lead to increased susceptibility to an induced infammation later in life in mice. Keywords C‑section delivery, Microbiota, Primary colonization, Early life, Infammation, Gut barrier, Murine modelinfo:eu-repo/semantics/publishedVersio

Gut barrier-microbiota imbalances in early life lead to higher sensitivity to inflammation in a murine model of C-section delivery

Most interactions between the host and its microbiota occur at the gut barrier, and primary colonizers are essential in the gut barrier maturation in the early life. The mother-offspring transmission of microorganisms is the most important factor influencing microbial colonization in mammals, and C-section delivery (CSD) is an important disruptive factor of this transfer. Recently, the deregulation of symbiotic host-microbe interactions in early life has been shown to alter the maturation of the immune system, predisposing the host to gut barrier dysfunction and inflammation. The main goal of this study is to decipher the role of the early-life gut microbiota-barrier alterations and its links with later-life risks of intestinal inflammation in a murine model of CSD. The higher sensitivity to chemically induced inflammation in CSD mice is related to excessive exposure to a too diverse microbiota too early in life. This early microbial stimulus has short-term consequences on the host homeostasis. It switches the pup's immune response to an inflammatory context and alters the epithelium structure and the mucus-producing cells, disrupting gut homeostasis. This presence of a too diverse microbiota in the very early life involves a disproportionate short-chain fatty acids ratio and an excessive antigen exposure across the vulnerable gut barrier in the first days of life, before the gut closure. Besides, as shown by microbiota transfer experiments, the microbiota is causal in the high sensitivity of CSD mice to chemical-induced colitis and in most of the phenotypical parameters found altered in early life. Finally, supplementation with lactobacilli, the main bacterial group impacted by CSD in mice, reverts the higher sensitivity to inflammation in ex-germ-free mice colonized by CSD pups' microbiota. Early-life gut microbiota-host crosstalk alterations related to CSD could be the linchpin behind the phenotypic effects that lead to increased susceptibility to an induced inflammation later in life in mice

Índice de sustentabilidade agroambiental para o perímetro irrigado Ayres de Souza.

Uma análise integrada do atual uso dos recursos naturais do Perímetro Irrigado de Ayres de Souza, localizado no Vale do Acaraú, Ceará, foi realizada através do desenvolvimento de um índice de sustentabilidade agroecológica. Os dados dessa pesquisa foram oriundos de questionários aplicados a 33 produtores agrícolas beneficiados pelo projeto de irrigação. Os indicadores de sustentabilidade foram estimados pelo emprego de análise fatorial, método da análise fatorial/análise de componentes principais. O índice de sustentabilidade estimado a partir dos indicadores selecionados registrou uma situação de sustentabilidade fragilizada ou de insustentabilidade reversível. As unidades produtivas apresentaram um porcentual de 60,6% com alguma sustentabilidade; e os demais 39,4% estão em condições de insustentabilidade. Os resultados também mostraram que os fatores dominantes do índice de sustentabilidade foram: nível da atividade agrícola praticada, agricultura familiar, condições atuais do sistema água-solo e infraestrutura,fontes alternativas de renda e experiência em tratos culturais

Transformational capacity and the influence of place and identity

Climate change is altering the productivity of natural resources with far-reaching implications for those who depend on them. Resource-dependent industries and communities need the capacity to adapt to a range of climate risks if they are to remain viable. In some instances, the scale and nature of the likely impacts means that transformations of function or structure will be required. Transformations represent a switch to a distinct new system where a different suite of factors become important in the design and implementation of response strategies. There is a critical gap in knowledge on understanding transformational capacity and its influences. On the basis of current knowledge on adaptive capacity we propose four foundations for measuring transformational capacity: (1)how risks and uncertainty are managed, (2)the extent of skills in planning, learning and reorganizing, (3)the level of financial and psychological flexibility to undertake change and (4)the willingness to undertake change. We test the influence of place attachment and occupational identity on transformational capacity using the Australian peanut industry, which is presently assessing significant structural change in response to predicted climatic changes. Survey data from 88% of peanut farmers in Queensland show a strong negative correlation between transformational capacity and both place attachment and occupational attachment, suggesting that whilst these factors may be important positive influences on the capacity to adapt to incremental change, they act as barriers to transformational change

Cortical fast-spiking parvalbumin interneurons enwrapped in the perineuronal net express the metallopeptidases Adamts8, Adamts15 and Neprilysin.

The in situ hybridization Allen Mouse Brain Atlas was mined for proteases expressed in the somatosensory cerebral cortex. Among the 480 genes coding for protease/peptidases, only four were found enriched in cortical interneurons: Reln coding for reelin; Adamts8 and Adamts15 belonging to the class of metzincin proteases involved in reshaping the perineuronal net (PNN) and Mme encoding for Neprilysin, the enzyme degrading amyloid β-peptides. The pattern of expression of metalloproteases (MPs) was analyzed by single-cell reverse transcriptase multiplex PCR after patch clamp and was compared with the expression of 10 canonical interneurons markers and 12 additional genes from the Allen Atlas. Clustering of these genes by K-means algorithm displays five distinct clusters. Among these five clusters, two fast-spiking interneuron clusters expressing the calcium-binding protein Pvalb were identified, one co-expressing Pvalb with Sst (PV-Sst) and another co-expressing Pvalb with three metallopeptidases Adamts8, Adamts15 and Mme (PV-MP). By using Wisteria floribunda agglutinin, a specific marker for PNN, PV-MP interneurons were found surrounded by PNN, whereas the ones expressing Sst, PV-Sst, were not

The Neuronal Transition Probability (NTP) Model for the Dynamic Progression of Non-REM Sleep EEG: The Role of the Suprachiasmatic Nucleus

Little attention has gone into linking to its neuronal substrates the dynamic structure of non-rapid-eye-movement (NREM) sleep, defined as the pattern of time-course power in all frequency bands across an entire episode. Using the spectral power time-courses in the sleep electroencephalogram (EEG), we showed in the typical first episode, several moves towards-and-away from deep sleep, each having an identical pattern linking the major frequency bands beta, sigma and delta. The neuronal transition probability model (NTP) – in fitting the data well – successfully explained the pattern as resulting from stochastic transitions of the firing-rates of the thalamically-projecting brainstem-activating neurons, alternating between two steady dynamic-states (towards-and-away from deep sleep) each initiated by a so-far unidentified flip-flop. The aims here are to identify this flip-flop and to demonstrate that the model fits well all NREM episodes, not just the first. Using published data on suprachiasmatic nucleus (SCN) activity we show that the SCN has the information required to provide a threshold-triggered flip-flop for timing the towards-and-away alternations, information provided by sleep-relevant feedback to the SCN. NTP then determines the pattern of spectral power within each dynamic-state. NTP was fitted to individual NREM episodes 1–4, using data from 30 healthy subjects aged 20–30 years, and the quality of fit for each NREM measured. We show that the model fits well all NREM episodes and the best-fit probability-set is found to be effectively the same in fitting all subject data. The significant model-data agreement, the constant probability parameter and the proposed role of the SCN add considerable strength to the model. With it we link for the first time findings at cellular level and detailed time-course data at EEG level, to give a coherent picture of NREM dynamics over the entire night and over hierarchic brain levels all the way from the SCN to the EEG

Circuit-based interrogation of sleep control.

Sleep is a fundamental biological process observed widely in the animal kingdom, but the neural circuits generating sleep remain poorly understood. Understanding the brain mechanisms controlling sleep requires the identification of key neurons in the control circuits and mapping of their synaptic connections. Technical innovations over the past decade have greatly facilitated dissection of the sleep circuits. This has set the stage for understanding how a variety of environmental and physiological factors influence sleep. The ability to initiate and terminate sleep on command will also help us to elucidate its functions within and beyond the brain

A Conserved Behavioral State Barrier Impedes Transitions between Anesthetic-Induced Unconsciousness and Wakefulness: Evidence for Neural Inertia

One major unanswered question in neuroscience is how the brain transitions between conscious and unconscious states. General anesthetics offer a controllable means to study these transitions. Induction of anesthesia is commonly attributed to drug-induced global modulation of neuronal function, while emergence from anesthesia has been thought to occur passively, paralleling elimination of the anesthetic from its sites in the central nervous system (CNS). If this were true, then CNS anesthetic concentrations on induction and emergence would be indistinguishable. By generating anesthetic dose-response data in both insects and mammals, we demonstrate that the forward and reverse paths through which anesthetic-induced unconsciousness arises and dissipates are not identical. Instead they exhibit hysteresis that is not fully explained by pharmacokinetics as previously thought. Single gene mutations that affect sleep-wake states are shown to collapse or widen anesthetic hysteresis without obvious confounding effects on volatile anesthetic uptake, distribution, or metabolism. We propose a fundamental and biologically conserved concept of neural inertia, a tendency of the CNS to resist behavioral state transitions between conscious and unconscious states. We demonstrate that such a barrier separates wakeful and anesthetized states for multiple anesthetics in both flies and mice, and argue that it contributes to the hysteresis observed when the brain transitions between conscious and unconscious states

Modeling complex ecological economic systems: toward an evolutionary, dynamic understanding of people and nature

Recent understanding about system dynamics and predictability that has emerged from the study of complex systems is creating new tools for modeling interactions between anthropogenic and natural systems. A range of techniques has become available through advances in computer speed and accessibility and by implementing a broad, interdisciplinary systems view